1 00:00:02,360 --> 00:00:05,880 Speaker 1: Hi, this is Barry Ridhults. She's listening to Masters in 2 00:00:05,880 --> 00:00:11,000 Speaker 1: Business on Bloomberg Radio. Our full interview and podcast is 3 00:00:11,039 --> 00:00:15,840 Speaker 1: with Michelle Myers. Uh. She is the deputy economist for 4 00:00:16,040 --> 00:00:20,520 Speaker 1: North America for Bank America Merrill Lynch. She really is 5 00:00:20,520 --> 00:00:24,599 Speaker 1: a very interesting person. It's rare these days to find 6 00:00:25,160 --> 00:00:30,040 Speaker 1: someone who as as accomplished as she is at such 7 00:00:30,080 --> 00:00:32,440 Speaker 1: a young age. She's in the thirties and she has 8 00:00:32,479 --> 00:00:35,360 Speaker 1: a role at a what effectively is one of the 9 00:00:35,360 --> 00:00:40,680 Speaker 1: biggest investment firms in the world. UM. I know her 10 00:00:40,720 --> 00:00:42,880 Speaker 1: for a few years from mutual friends. I think I 11 00:00:42,960 --> 00:00:46,239 Speaker 1: might have first met her through Dave Rosenberg and a 12 00:00:46,280 --> 00:00:50,959 Speaker 1: few other folks who are either economists or researchers. Um. 13 00:00:51,080 --> 00:00:55,280 Speaker 1: She's actually a delightful person and really really knowledgeable about things. 14 00:00:55,360 --> 00:01:00,000 Speaker 1: I think she brings a very very fundamental approach to economics. 15 00:01:00,040 --> 00:01:03,440 Speaker 1: She's a bit of a data wank. Really interesting background. 16 00:01:03,680 --> 00:01:08,039 Speaker 1: Uh double uh degree Masters and bachelors in four years 17 00:01:08,080 --> 00:01:11,720 Speaker 1: from Boston University, which is really very very impressive to 18 00:01:11,760 --> 00:01:17,080 Speaker 1: do that. She is an expert on both the housing market, 19 00:01:17,200 --> 00:01:20,080 Speaker 1: which she's covered for many years, as well as the 20 00:01:20,160 --> 00:01:25,120 Speaker 1: labor market, and and those are two UM. Terrific qualifications 21 00:01:25,160 --> 00:01:27,920 Speaker 1: to have if you're an economist covering the United States 22 00:01:28,560 --> 00:01:33,440 Speaker 1: UH in the post credit crisis era. Her background is simply, 23 00:01:34,080 --> 00:01:37,600 Speaker 1: she came out of school and went right to Lehman Brothers. 24 00:01:37,640 --> 00:01:41,000 Speaker 1: She was there right in the middle of the crisis. 25 00:01:41,040 --> 00:01:43,400 Speaker 1: I wish we had more time to discuss that with her, 26 00:01:43,480 --> 00:01:47,360 Speaker 1: but she described it. It was really quite fascinating what 27 00:01:47,680 --> 00:01:49,360 Speaker 1: it was like to be in the eye of the 28 00:01:49,440 --> 00:01:53,440 Speaker 1: hurricane during that that collapse. Um stayed on at Barkley's 29 00:01:53,480 --> 00:01:57,120 Speaker 1: when they took over Lehman Brothers post bankruptcy, and her 30 00:01:57,240 --> 00:02:01,560 Speaker 1: former boss, Ethan Harris at Lehman Brothers, ended up taking 31 00:02:01,600 --> 00:02:07,400 Speaker 1: over the lead economist role at Merrill Lynch and ultimately 32 00:02:07,480 --> 00:02:10,800 Speaker 1: ended up recruiting her to join him at Maryland. So 33 00:02:10,919 --> 00:02:14,560 Speaker 1: he's been at that position. She's been at that position 34 00:02:14,600 --> 00:02:17,440 Speaker 1: at Merrill Lynch now for about five years. So, without 35 00:02:17,480 --> 00:02:21,800 Speaker 1: any further ado, here is my conversation with Michelle Myers 36 00:02:22,400 --> 00:02:29,120 Speaker 1: of Merrill Lynch. This is Master's in Business with Barry 37 00:02:29,240 --> 00:02:34,160 Speaker 1: Ridholts on Bloomberg Radio. My guest this week is Michelle Meyer. 38 00:02:34,400 --> 00:02:38,040 Speaker 1: She is the deputy head of economics for Merrill Lynch 39 00:02:38,120 --> 00:02:40,240 Speaker 1: for the United States let me give you a little 40 00:02:40,280 --> 00:02:45,920 Speaker 1: background about Michelle UM Undergraduate Boston University. You did a 41 00:02:46,040 --> 00:02:48,600 Speaker 1: joint B A M A program, Is that right? I 42 00:02:48,639 --> 00:02:52,079 Speaker 1: did in four years? Four years so I started taking 43 00:02:52,080 --> 00:02:55,200 Speaker 1: my graduate coursework my junior year of undergrads. You can 44 00:02:55,200 --> 00:02:57,720 Speaker 1: imagine how exciting my social life was my junior year 45 00:02:58,160 --> 00:03:00,200 Speaker 1: and he was a five year program. But that you 46 00:03:00,240 --> 00:03:03,640 Speaker 1: did it for there you go, So zero social life? 47 00:03:03,639 --> 00:03:06,359 Speaker 1: Did you? Was it? Twenty four hours a day? Summer 48 00:03:06,440 --> 00:03:08,600 Speaker 1: is the whole deal? Just now. Luckily I didn't have 49 00:03:08,760 --> 00:03:12,280 Speaker 1: to have school in the summer because I had a 50 00:03:12,320 --> 00:03:13,840 Speaker 1: lot of credits heading in, so I would have been 51 00:03:13,840 --> 00:03:16,680 Speaker 1: able to graduate underground in three years. So so let 52 00:03:16,760 --> 00:03:18,760 Speaker 1: me give people a little background about who you are 53 00:03:18,760 --> 00:03:22,360 Speaker 1: and what you do for a living. You're essentially the 54 00:03:22,440 --> 00:03:26,800 Speaker 1: chief economists for the United States for Merrill Lynch, one 55 00:03:26,840 --> 00:03:30,320 Speaker 1: of the biggest, if not the biggest, of American Bank 56 00:03:30,360 --> 00:03:33,320 Speaker 1: of America Merrill Lynch. That's right. I'm still stuck in 57 00:03:33,360 --> 00:03:37,600 Speaker 1: the two thousand's. I have a pre crisis mindset. You 58 00:03:37,640 --> 00:03:41,800 Speaker 1: were named to Forbes list of thirty under thirty and Finance. 59 00:03:42,080 --> 00:03:44,440 Speaker 1: That was a couple of years ago. So now you 60 00:03:44,680 --> 00:03:47,680 Speaker 1: more recently were named to thirty five under thirty five 61 00:03:48,640 --> 00:03:51,760 Speaker 1: not too long ago. UM, and you have a really 62 00:03:51,800 --> 00:03:55,680 Speaker 1: interesting background. You were at Lehman Brothers right throughout the crisis, 63 00:03:55,760 --> 00:03:58,640 Speaker 1: then that became Barclays, and then for the past five 64 00:03:58,720 --> 00:04:01,880 Speaker 1: years you've been at Meryl. So let's talk a little 65 00:04:01,880 --> 00:04:05,080 Speaker 1: bit about about your background. So you have a master's 66 00:04:05,720 --> 00:04:09,240 Speaker 1: and a b a. In economics. What made you think, well, 67 00:04:09,320 --> 00:04:11,120 Speaker 1: let's go to Wall Street and work for some of 68 00:04:11,160 --> 00:04:14,720 Speaker 1: the biggest names, most storied names on the street. Well, 69 00:04:14,760 --> 00:04:17,720 Speaker 1: who wouldn't want to do that? Um? Lots lots of 70 00:04:17,720 --> 00:04:21,440 Speaker 1: people think finances a little squishy and they go elsewhere. No, 71 00:04:21,560 --> 00:04:24,039 Speaker 1: I understand, I understand. You know. Frankly, at the time, 72 00:04:24,080 --> 00:04:26,800 Speaker 1: I didn't know what I wanted to do. I graduated 73 00:04:27,160 --> 00:04:30,280 Speaker 1: from graduate school and I actually intended to go straight 74 00:04:30,320 --> 00:04:35,400 Speaker 1: through for a PhD. I had a wonderful UM advisor 75 00:04:35,680 --> 00:04:39,279 Speaker 1: UM at school, professor Kevin Lang, who was actually a 76 00:04:39,320 --> 00:04:42,839 Speaker 1: micro economist focusing on labor markets, and that was my 77 00:04:42,920 --> 00:04:45,240 Speaker 1: area focus was labor economics, the micro side, not the 78 00:04:45,279 --> 00:04:47,359 Speaker 1: macro side. So that's really funny because I think of 79 00:04:47,400 --> 00:04:50,800 Speaker 1: you as a housing and real estate specialty, not so 80 00:04:50,880 --> 00:04:53,400 Speaker 1: much labor. That's true, and what I do now is 81 00:04:53,440 --> 00:04:56,040 Speaker 1: much more macro focus. It's markets focused. But what I 82 00:04:56,040 --> 00:05:00,359 Speaker 1: was studying was was was micro UM and UM I 83 00:05:00,400 --> 00:05:03,400 Speaker 1: spoke to him and he advised, you know, go into 84 00:05:03,440 --> 00:05:05,960 Speaker 1: the workforce, figure out what you want to do, figure 85 00:05:05,960 --> 00:05:08,680 Speaker 1: out what you can do with the skill set UM 86 00:05:08,720 --> 00:05:11,479 Speaker 1: and then if if it seems appropriate, comeback and pursue 87 00:05:11,520 --> 00:05:14,520 Speaker 1: a higher degree. But it's not necessarily the right path 88 00:05:14,640 --> 00:05:18,080 Speaker 1: for everyone. And UM I think oftentimes when you're in school, 89 00:05:18,080 --> 00:05:19,880 Speaker 1: when you're studying, you get so focused on what that 90 00:05:19,960 --> 00:05:22,960 Speaker 1: next step is for your education. Sometimes you forgotten what 91 00:05:23,000 --> 00:05:24,640 Speaker 1: am I actually going to do with this, what should 92 00:05:24,680 --> 00:05:25,960 Speaker 1: I be doing with and what am I good at? 93 00:05:26,000 --> 00:05:29,360 Speaker 1: Where are my talents? So UM I took about a 94 00:05:29,480 --> 00:05:33,520 Speaker 1: year after I graduated UM before entering the industry, and 95 00:05:33,560 --> 00:05:38,479 Speaker 1: then I applied for jobs at bult bracket Wall Street 96 00:05:38,480 --> 00:05:41,240 Speaker 1: firms only in their economics department, so not through the 97 00:05:41,240 --> 00:05:45,880 Speaker 1: typical analyst class. UM I applied to economic consulting firms 98 00:05:45,880 --> 00:05:48,480 Speaker 1: such as Nara for example, and I was at the end, 99 00:05:48,520 --> 00:05:50,479 Speaker 1: I was between Nara and Lehman when it came down 100 00:05:50,480 --> 00:05:53,280 Speaker 1: to it. And then I I also would have loved 101 00:05:53,279 --> 00:05:55,160 Speaker 1: have gone into policy and one of my regrets is 102 00:05:55,200 --> 00:05:56,960 Speaker 1: that I actually didn't go to the federalies. Or first, 103 00:05:56,960 --> 00:05:58,720 Speaker 1: I think that's a great opportunity that I didn't get 104 00:05:58,760 --> 00:06:02,000 Speaker 1: at the time. Um. But I was lucky enough, fortunate 105 00:06:02,120 --> 00:06:04,640 Speaker 1: enough to have an offer at Lean Brothers to join 106 00:06:04,680 --> 00:06:07,560 Speaker 1: as a lateral higher in their economics group. So one 107 00:06:07,600 --> 00:06:09,400 Speaker 1: thing I knew, one thing I figured out is that 108 00:06:09,440 --> 00:06:12,320 Speaker 1: I loved economics and I wanted to do something purely 109 00:06:12,400 --> 00:06:17,600 Speaker 1: in economics. So who were your early mentors at Lehman Brothers. Um, 110 00:06:17,640 --> 00:06:20,400 Speaker 1: what I'd obviously have to say, my boss. Then who's 111 00:06:20,480 --> 00:06:23,560 Speaker 1: my boss now? Ethan Harris? Um? He was the chief 112 00:06:23,640 --> 00:06:26,280 Speaker 1: US economist at Lehman when I joined. And he's wait 113 00:06:26,320 --> 00:06:30,360 Speaker 1: a second, Ethan's the chief US economist chief economists at 114 00:06:30,720 --> 00:06:33,440 Speaker 1: Bank America Merrill Lynch right now. He is the he 115 00:06:33,520 --> 00:06:36,040 Speaker 1: is a co head of global economics. Did you come 116 00:06:36,040 --> 00:06:38,479 Speaker 1: over from Lehman's Merrow with him as part of a 117 00:06:38,520 --> 00:06:41,160 Speaker 1: team or is this just coincidence? Um, it's not conscidence. 118 00:06:41,200 --> 00:06:43,679 Speaker 1: But I did not come. I did not go with him. Um. 119 00:06:43,760 --> 00:06:47,560 Speaker 1: So I I state at Barkley's. Um. After Lehman went under, 120 00:06:47,920 --> 00:06:52,040 Speaker 1: and Barkley's took for those people to remember post bankruptcy filing, 121 00:06:52,040 --> 00:06:56,800 Speaker 1: Barkley's essentially took over all of Lehman Brothers at very 122 00:06:56,839 --> 00:06:59,400 Speaker 1: advantageous cost. It was great. It was a great deal 123 00:06:59,440 --> 00:07:01,599 Speaker 1: for Barkley. Yeah, at the time it was hard to 124 00:07:01,600 --> 00:07:04,720 Speaker 1: see how anything was great. But in retrospect, yes, that's 125 00:07:04,760 --> 00:07:08,240 Speaker 1: that's that's exactly right. And more about the financial crisis later, 126 00:07:08,279 --> 00:07:12,160 Speaker 1: because you were right in the hurricanes. Oh, I was um. 127 00:07:12,160 --> 00:07:13,880 Speaker 1: But I was fortunate enough to move over to Berkley 128 00:07:13,880 --> 00:07:16,640 Speaker 1: as they stayed there for some time, and then Ethan 129 00:07:17,080 --> 00:07:19,600 Speaker 1: recruited me back to work with him again at and Merrow, 130 00:07:19,600 --> 00:07:22,400 Speaker 1: which has been a great, great move for me. So Um. 131 00:07:22,440 --> 00:07:24,440 Speaker 1: Of course he is clearly one of my mentors. I've 132 00:07:24,480 --> 00:07:26,000 Speaker 1: learned a lot from him in terms of how to 133 00:07:26,040 --> 00:07:28,360 Speaker 1: be an economist on Wall Street. And there is a 134 00:07:28,360 --> 00:07:31,680 Speaker 1: lot to learn because it's one thing to understand economics 135 00:07:31,720 --> 00:07:34,520 Speaker 1: in theory. It's another thing to understand in terms of 136 00:07:34,560 --> 00:07:36,120 Speaker 1: what it means for the business and how to be 137 00:07:36,160 --> 00:07:39,520 Speaker 1: a market economists, and there's two distinct things. Other early 138 00:07:39,600 --> 00:07:43,200 Speaker 1: mentors I mean, I think the economics team overall I worked. 139 00:07:43,240 --> 00:07:45,760 Speaker 1: I got to work with Drew Maddie who's now UM 140 00:07:45,880 --> 00:07:48,880 Speaker 1: economist at a U B. S UM. He was quite 141 00:07:48,880 --> 00:07:50,800 Speaker 1: influential in my career. He really showed me the ropes. 142 00:07:50,840 --> 00:07:53,680 Speaker 1: He taught me what it meant to be a trading 143 00:07:53,680 --> 00:07:56,200 Speaker 1: for economist, how to understand the data, and how to 144 00:07:56,280 --> 00:07:59,960 Speaker 1: interact with the salesforce. John Shon, who was an economist 145 00:08:00,080 --> 00:08:02,480 Speaker 1: Leahman at the time. He's now an FX research at 146 00:08:02,480 --> 00:08:05,440 Speaker 1: Bank America Maryland. Show'm once again a colleague of his, 147 00:08:05,640 --> 00:08:10,120 Speaker 1: and he also was was was really influential in terms 148 00:08:10,160 --> 00:08:14,160 Speaker 1: of me understanding, um, what it meant to to to 149 00:08:14,440 --> 00:08:18,000 Speaker 1: produce quality research notes on Wall Street, but also be 150 00:08:18,120 --> 00:08:20,640 Speaker 1: shortened to the point. So those are kind of the 151 00:08:20,680 --> 00:08:23,679 Speaker 1: mentors in terms of strictly economics, but of course there's 152 00:08:23,760 --> 00:08:26,600 Speaker 1: these these broader, bigger mentors as well in the industry. 153 00:08:26,760 --> 00:08:28,720 Speaker 1: So what's your favorite We have a minute left in 154 00:08:28,720 --> 00:08:31,320 Speaker 1: the segment, what what's your favorite part of the job 155 00:08:31,480 --> 00:08:35,440 Speaker 1: as an economist at a big from m M. You know, 156 00:08:35,520 --> 00:08:38,120 Speaker 1: I think what's great about me economists on Wall Street 157 00:08:38,679 --> 00:08:41,560 Speaker 1: is that for me personally, I sit on the trading floor. 158 00:08:41,920 --> 00:08:45,479 Speaker 1: I get to be in the action. There's so much adrenaline. 159 00:08:45,520 --> 00:08:47,600 Speaker 1: The day goes by so quickly, so I get to 160 00:08:47,640 --> 00:08:49,960 Speaker 1: think about the big picture. I get to do research. 161 00:08:50,360 --> 00:08:54,120 Speaker 1: I keep up with the literature coming out of academia 162 00:08:54,240 --> 00:08:56,719 Speaker 1: and out of the federal Reserve banks. But I get 163 00:08:56,760 --> 00:08:59,080 Speaker 1: to apply it immediately and I see how the market 164 00:08:59,080 --> 00:09:01,719 Speaker 1: reacts to it. So I find that I have the 165 00:09:01,760 --> 00:09:04,920 Speaker 1: best of both worlds in that respect. Take us through 166 00:09:04,960 --> 00:09:07,520 Speaker 1: a day in the life for someone who has a 167 00:09:07,600 --> 00:09:11,120 Speaker 1: job like yours, working at a shop like Meryl. Sure, 168 00:09:11,360 --> 00:09:14,080 Speaker 1: so it starts early because the market start earlier and 169 00:09:14,120 --> 00:09:17,160 Speaker 1: there's morning meetings. You have to cover the data. Think 170 00:09:17,200 --> 00:09:23,480 Speaker 1: about what's going to influence define, define eily. Okay, you're 171 00:09:23,520 --> 00:09:27,840 Speaker 1: in the office. That's pretty that's pretty good. Yeah, and UM, 172 00:09:28,000 --> 00:09:29,880 Speaker 1: sit down, try to understand the data it's coming out 173 00:09:29,880 --> 00:09:33,120 Speaker 1: for the day. Talked to the salesforce, Um, talk to 174 00:09:33,120 --> 00:09:36,920 Speaker 1: the traders. So do the basic wrap. I have what's 175 00:09:36,960 --> 00:09:39,160 Speaker 1: called a hoot or it's like a microphone that I 176 00:09:39,200 --> 00:09:43,040 Speaker 1: go over when the data comes at squawk exactly what 177 00:09:43,160 --> 00:09:45,920 Speaker 1: they used to call hoot and holl exactly, which really 178 00:09:45,920 --> 00:09:47,560 Speaker 1: helps because if I was just to stand up and 179 00:09:47,559 --> 00:09:50,040 Speaker 1: try to shout, it would not at all be affective. 180 00:09:50,120 --> 00:09:53,800 Speaker 1: Do not have a voice that's going to penetrate allowed 181 00:09:53,880 --> 00:09:56,000 Speaker 1: room full of traders. No, I don't think I would. 182 00:09:56,080 --> 00:09:58,800 Speaker 1: I don't the trading floor and Meryl. For people who 183 00:09:58,880 --> 00:10:03,760 Speaker 1: haven't been downtown, that's a phenomenal space. I remember going 184 00:10:03,800 --> 00:10:07,520 Speaker 1: there for something fifteen years ago, and I'm sure it's changed. 185 00:10:07,559 --> 00:10:09,560 Speaker 1: The number. Well, when we've moved, Yeah, we're now we're 186 00:10:09,600 --> 00:10:13,440 Speaker 1: not midtown. Yeah, but you're right the downtown, You're absolutely right. 187 00:10:13,440 --> 00:10:15,839 Speaker 1: It's exceptionally large. It's like a football field. Now it's 188 00:10:15,880 --> 00:10:18,640 Speaker 1: a bit more manageable, and that the way they separate 189 00:10:18,679 --> 00:10:21,520 Speaker 1: the businesses, you can kind of but it's still used. 190 00:10:21,679 --> 00:10:24,440 Speaker 1: It's massive. It's it's massive. So you walk in and 191 00:10:24,440 --> 00:10:27,600 Speaker 1: it's like, wow, how does anybody get anything done here? Yeah, 192 00:10:27,640 --> 00:10:29,400 Speaker 1: it's but you know, you get you get used to it, 193 00:10:29,440 --> 00:10:32,559 Speaker 1: and in a certain, a certain extent that that buzz 194 00:10:32,559 --> 00:10:36,040 Speaker 1: on the training floor makes you more efficient and and 195 00:10:36,040 --> 00:10:38,240 Speaker 1: and and everybody else around you is picking up two 196 00:10:38,280 --> 00:10:40,880 Speaker 1: phones and has five screens, so you're doing the same 197 00:10:40,920 --> 00:10:44,400 Speaker 1: and and it's great. So the morning, I'm very much 198 00:10:44,440 --> 00:10:46,440 Speaker 1: focused on what's happening in terms of the data flow 199 00:10:46,440 --> 00:10:49,080 Speaker 1: of the markets, talking to clients, talking to sales and trading. 200 00:10:49,520 --> 00:10:52,560 Speaker 1: The afternoon things will quiet down a bit more client 201 00:10:52,679 --> 00:10:55,040 Speaker 1: meetings UM. Some as I'll go to the research floor 202 00:10:55,080 --> 00:10:56,880 Speaker 1: where it's a bit more quiet and I can write, 203 00:10:57,160 --> 00:10:59,880 Speaker 1: talk to the rest of the team UM and try 204 00:11:00,040 --> 00:11:02,920 Speaker 1: get our weekly publication out UM. Every week it's almost 205 00:11:02,920 --> 00:11:04,920 Speaker 1: like having a homework assignment. You have to write a 206 00:11:04,920 --> 00:11:07,719 Speaker 1: piece about what's happening in the economy, what's happening in 207 00:11:07,720 --> 00:11:09,440 Speaker 1: the markets, what our readers might care about. How do 208 00:11:09,440 --> 00:11:12,640 Speaker 1: you get anything written with all that buzz going on, 209 00:11:12,679 --> 00:11:15,559 Speaker 1: all that din So I think to a certain extent, again, 210 00:11:15,600 --> 00:11:18,120 Speaker 1: being on the train floor, being close to the action, 211 00:11:18,280 --> 00:11:20,480 Speaker 1: you you have a better understanding of what's important and 212 00:11:20,480 --> 00:11:23,520 Speaker 1: what our clients are talking about and what people want 213 00:11:23,559 --> 00:11:26,079 Speaker 1: to understand. So you get inspired by sitting on the 214 00:11:26,120 --> 00:11:29,480 Speaker 1: training floor and in terms of getting out relevant research. 215 00:11:29,880 --> 00:11:31,800 Speaker 1: But you're right when when you have to read through 216 00:11:31,800 --> 00:11:33,959 Speaker 1: papers and you have to actually put pen to paper, 217 00:11:34,000 --> 00:11:36,240 Speaker 1: oftentimes you do need to remove yourself from the floor, 218 00:11:36,320 --> 00:11:38,200 Speaker 1: which of course I do. I'll either go to a 219 00:11:38,200 --> 00:11:41,280 Speaker 1: research floor or sometimes I get my best work done 220 00:11:41,600 --> 00:11:44,480 Speaker 1: at night after I have dinner. It's quiet, from you know, 221 00:11:44,559 --> 00:11:47,120 Speaker 1: eight o'clock to nine o'clock. I can sit and write 222 00:11:47,200 --> 00:11:50,560 Speaker 1: and I do right. I find the early morning hours 223 00:11:50,559 --> 00:11:52,920 Speaker 1: are are just perfect for that. There's no more early 224 00:11:52,960 --> 00:11:57,080 Speaker 1: morning hours for me. That four thirty is nothing going on. 225 00:11:57,120 --> 00:11:59,760 Speaker 1: It's great. So so let's talk a little bit. You 226 00:12:00,040 --> 00:12:02,600 Speaker 1: are only the second woman we've had as a guest. 227 00:12:02,640 --> 00:12:04,920 Speaker 1: We have Liz and Sonders scheduled for later this spring. 228 00:12:05,280 --> 00:12:08,640 Speaker 1: I am honored. Well, we've been trying to bring more 229 00:12:08,640 --> 00:12:12,560 Speaker 1: people who are not white males as as guests, and 230 00:12:12,760 --> 00:12:16,560 Speaker 1: it's kind of hard to find people at a certain 231 00:12:16,760 --> 00:12:20,080 Speaker 1: level on Wall Street who aren't part of the old 232 00:12:20,080 --> 00:12:22,840 Speaker 1: Boys network. So let's first talk about you know, I 233 00:12:22,840 --> 00:12:25,360 Speaker 1: want to give you a quote from you that was 234 00:12:25,400 --> 00:12:29,280 Speaker 1: pretty relevant. You said, when an opportunity presents itself that 235 00:12:29,440 --> 00:12:34,600 Speaker 1: is challenging, uncomfortable, intimidating, or makes you want to hide 236 00:12:34,640 --> 00:12:38,120 Speaker 1: unto the table, that's just the sort of opportunity you 237 00:12:38,160 --> 00:12:41,240 Speaker 1: have to take. Yeah, so discuss that. I stand by 238 00:12:41,280 --> 00:12:44,280 Speaker 1: those words. I think oftentimes, and perhaps it's more so 239 00:12:44,440 --> 00:12:46,240 Speaker 1: for women than for men, I don't know. I think 240 00:12:46,240 --> 00:12:50,280 Speaker 1: it spends on the individual, but oftentimes you shy away 241 00:12:50,280 --> 00:12:53,679 Speaker 1: from opportunities that are intimidating, that scare you, that make 242 00:12:53,720 --> 00:12:56,000 Speaker 1: your heart sink, But those are oftentimes where you have 243 00:12:56,240 --> 00:12:59,560 Speaker 1: the best career advancement. So one of the things for 244 00:12:59,559 --> 00:13:03,640 Speaker 1: for me I was media. When I started getting opportunities 245 00:13:03,679 --> 00:13:05,679 Speaker 1: to go on on TV, it was actually I was 246 00:13:05,679 --> 00:13:07,480 Speaker 1: still at Lehman Brothers, so I was fairly new to 247 00:13:08,160 --> 00:13:11,440 Speaker 1: this industry, was really new to the job, and um, 248 00:13:11,480 --> 00:13:14,720 Speaker 1: you know, whenever a producer recalled, I would be intimidated. 249 00:13:15,080 --> 00:13:17,320 Speaker 1: My gosh, maybe maybe the timing won't work out, maybe 250 00:13:17,320 --> 00:13:19,200 Speaker 1: I don't have to do it, because it was so 251 00:13:19,360 --> 00:13:22,240 Speaker 1: nerve racking to me. But that I think has certainly 252 00:13:22,280 --> 00:13:26,200 Speaker 1: been one of the major things I've supported my career 253 00:13:26,320 --> 00:13:29,880 Speaker 1: is visibility, and it helps me in terms of being 254 00:13:29,880 --> 00:13:32,920 Speaker 1: able to communicate and being a more effective economist. So 255 00:13:33,040 --> 00:13:35,679 Speaker 1: let me give you another quote of your own. You 256 00:13:35,760 --> 00:13:38,880 Speaker 1: once said, the lack of women at the top of 257 00:13:38,920 --> 00:13:42,160 Speaker 1: the industry is a challenge for women in finance, So 258 00:13:42,240 --> 00:13:44,600 Speaker 1: explain what you mean by that. Well, I think, particularly 259 00:13:44,640 --> 00:13:49,000 Speaker 1: for me starting out at Lehman Brothers, UM, I felt 260 00:13:49,080 --> 00:13:51,960 Speaker 1: that there weren't that many role models. So a lot 261 00:13:52,000 --> 00:13:55,520 Speaker 1: of the senior management were men um and even kind 262 00:13:55,520 --> 00:13:58,559 Speaker 1: of most all um and even the mid level, like 263 00:13:58,640 --> 00:14:01,560 Speaker 1: the higher mid level, where heavily dominated by by men. 264 00:14:01,679 --> 00:14:05,040 Speaker 1: So it was hard to understand looking ahead, how do 265 00:14:05,080 --> 00:14:08,319 Speaker 1: you are there? Things are there unknowns? Right? Are there? 266 00:14:08,320 --> 00:14:10,560 Speaker 1: Things that are ultimately going to make it impossible for 267 00:14:10,600 --> 00:14:13,640 Speaker 1: me to achieve success here because other women have not 268 00:14:13,720 --> 00:14:17,040 Speaker 1: succeeded and you don't know. Maybe it's because their number 269 00:14:17,040 --> 00:14:19,280 Speaker 1: of factors for why that might be. But as a 270 00:14:19,280 --> 00:14:22,160 Speaker 1: young woman starting out, I think it could be discouraging 271 00:14:22,200 --> 00:14:25,000 Speaker 1: when you don't see other people that you could relate 272 00:14:25,040 --> 00:14:27,000 Speaker 1: to that are in senior roles. And one of the 273 00:14:27,040 --> 00:14:29,040 Speaker 1: things I have to say is a lot has changed 274 00:14:29,120 --> 00:14:32,240 Speaker 1: over those tres. Literally my next question, what's changed over 275 00:14:32,280 --> 00:14:35,320 Speaker 1: the best A lot? I mean to me, it's I 276 00:14:35,440 --> 00:14:38,160 Speaker 1: promise I'm not looking at your sheet. Um. I think 277 00:14:38,160 --> 00:14:40,800 Speaker 1: there's been much advancement, and maybe it's simply moving from 278 00:14:40,840 --> 00:14:42,960 Speaker 1: Lehman to b of A. But here at b A, 279 00:14:43,240 --> 00:14:45,720 Speaker 1: I have a number of senior role models that are women. 280 00:14:45,760 --> 00:14:50,080 Speaker 1: The head of research, Ethan's boss, Kennice Browning. Um, she's 281 00:14:50,080 --> 00:14:52,880 Speaker 1: an exceptional's been there for quite a while, right, She's 282 00:14:52,880 --> 00:14:55,720 Speaker 1: been had a research for at least. We're mutual friends 283 00:14:55,720 --> 00:14:59,000 Speaker 1: with Dave Rosenberg, who used to be had Ethan's job 284 00:14:59,480 --> 00:15:02,400 Speaker 1: a few before him, and I think I met her 285 00:15:02,440 --> 00:15:05,040 Speaker 1: through him. I want to say it's a decade ago. 286 00:15:05,760 --> 00:15:08,800 Speaker 1: She's been a very senior female on Wall Street for 287 00:15:08,840 --> 00:15:11,160 Speaker 1: a long long time. Supposed to be a tough cookie too. 288 00:15:12,120 --> 00:15:14,480 Speaker 1: I think she's incredibly good at her job, and she 289 00:15:14,560 --> 00:15:16,920 Speaker 1: understands the business, and she understands what it means to 290 00:15:16,960 --> 00:15:19,760 Speaker 1: be an analyst, and I think she understands how to 291 00:15:19,920 --> 00:15:23,320 Speaker 1: how to how to get appropriate balance. So seeing her 292 00:15:23,680 --> 00:15:26,960 Speaker 1: have success has been, UM, really important to me. And 293 00:15:26,960 --> 00:15:29,520 Speaker 1: it's and and and it's it's also across the cross 294 00:15:29,520 --> 00:15:32,480 Speaker 1: the business. I can count a number of senior women 295 00:15:32,520 --> 00:15:35,160 Speaker 1: at Bank of America, Mary Lynch that kind of have 296 00:15:35,280 --> 00:15:37,760 Speaker 1: done it all and and and and frankly, I now 297 00:15:37,800 --> 00:15:40,560 Speaker 1: consider myself to be in that camp. Well, you were 298 00:15:40,560 --> 00:15:46,040 Speaker 1: promoted to managing director at B A m L fairly young? Yes, yeah, 299 00:15:46,160 --> 00:15:48,920 Speaker 1: And was that process like? Was that was that a surprise? 300 00:15:49,080 --> 00:15:51,440 Speaker 1: Was that exciting? Um? Well, it wasn't surprised because I 301 00:15:51,480 --> 00:15:53,480 Speaker 1: had to advocate for myself. You always have to advocate 302 00:15:53,480 --> 00:15:57,320 Speaker 1: for yourself. It doesn't just happen by accident. Um. But 303 00:15:57,400 --> 00:15:59,920 Speaker 1: I did that. And UM. One of the things that 304 00:16:00,080 --> 00:16:02,000 Speaker 1: I realized very quickly is that I had a very 305 00:16:02,080 --> 00:16:08,200 Speaker 1: large support network. Um Many particularly women stood up and said, 306 00:16:08,320 --> 00:16:12,160 Speaker 1: you know you, you are very talented and you should 307 00:16:12,240 --> 00:16:15,120 Speaker 1: and will be successful, and you deserve the recognition of 308 00:16:15,160 --> 00:16:17,520 Speaker 1: managing directors. So I had a lot of support from 309 00:16:17,520 --> 00:16:19,960 Speaker 1: women across the business, but also you know, number of 310 00:16:20,120 --> 00:16:23,440 Speaker 1: obviously men as well and in senior positions, and it 311 00:16:23,520 --> 00:16:26,520 Speaker 1: was it was a very enlightening process for me. The 312 00:16:26,520 --> 00:16:29,600 Speaker 1: managing director process, it's a hard process. You have to 313 00:16:29,640 --> 00:16:34,080 Speaker 1: have a network of supporters and almost like a doctoral dissertation, 314 00:16:34,120 --> 00:16:38,120 Speaker 1: and before the committee it's very competitive. We were beginning 315 00:16:38,120 --> 00:16:41,400 Speaker 1: to discuss what it was like being a Lehman Brothers 316 00:16:41,560 --> 00:16:44,320 Speaker 1: right out of school, but less fast forward a couple 317 00:16:44,320 --> 00:16:48,720 Speaker 1: of years, you were there right through everything hitting the fan. 318 00:16:49,480 --> 00:16:52,800 Speaker 1: What was it like in the midst of Lehman Brothers 319 00:16:53,400 --> 00:16:56,280 Speaker 1: during two thousand and eight there was just a great 320 00:16:56,320 --> 00:17:01,200 Speaker 1: deal of uncertainty, and that uncertainty ultimately translate to panic. 321 00:17:01,720 --> 00:17:05,640 Speaker 1: Um we all kind of an idea that there were 322 00:17:06,119 --> 00:17:10,080 Speaker 1: problems in the housing market, their problems in the financial system. 323 00:17:10,119 --> 00:17:14,360 Speaker 1: After bear Sterns went under. Let's let's put that into 324 00:17:14,359 --> 00:17:17,400 Speaker 1: a little context. In oh seven, a fairly leveraged bear 325 00:17:17,440 --> 00:17:21,040 Speaker 1: Sterns pair of hedge funds that mostly focused on mortgage 326 00:17:21,040 --> 00:17:24,960 Speaker 1: backed and other credit derivatives blew up, and then bear 327 00:17:25,000 --> 00:17:27,240 Speaker 1: Sterns got a little wobbly, and then in the spring 328 00:17:27,560 --> 00:17:30,720 Speaker 1: bear Sterns ended up going down in last minute, taken 329 00:17:30,760 --> 00:17:34,320 Speaker 1: over by JP Morgan for originally two dollars a year, 330 00:17:34,359 --> 00:17:36,399 Speaker 1: and then I think it ended up being ten dollars 331 00:17:36,400 --> 00:17:39,400 Speaker 1: a year. And after Bear went down, everybody said, well, 332 00:17:39,440 --> 00:17:43,359 Speaker 1: who did looks similar to Bear? And Lehman was the 333 00:17:43,400 --> 00:17:46,359 Speaker 1: next in size and a lot of similar paper and 334 00:17:46,359 --> 00:17:49,000 Speaker 1: and swamming a lout of the same waters. But did 335 00:17:49,000 --> 00:17:51,719 Speaker 1: anyone there really have They did a lot of mortgage 336 00:17:51,760 --> 00:17:54,320 Speaker 1: backed and a lot of securitized things, but did anyone 337 00:17:54,440 --> 00:17:56,879 Speaker 1: their day to day did Was there really a sense 338 00:17:56,960 --> 00:18:00,000 Speaker 1: that the whole shooting match is gonna come tumbling down? 339 00:18:00,000 --> 00:18:03,119 Speaker 1: Don't know where people really surprised by that. So I 340 00:18:03,160 --> 00:18:06,320 Speaker 1: think the initial view was that we were Lehman was 341 00:18:06,400 --> 00:18:09,639 Speaker 1: different than Bear Sterns, spare Sterns was somewhat unique, and 342 00:18:09,920 --> 00:18:13,359 Speaker 1: although Lehman had issues a lot of other financial institutions 343 00:18:13,640 --> 00:18:15,720 Speaker 1: had issues, they were manageable and we'd be able to 344 00:18:15,800 --> 00:18:18,399 Speaker 1: absorb the losses. UM I would say about a few 345 00:18:18,480 --> 00:18:24,840 Speaker 1: weeks before the d D, the bankruptcy UM see we're 346 00:18:24,840 --> 00:18:27,119 Speaker 1: talking of the summer. That's right. By the end of 347 00:18:27,160 --> 00:18:29,360 Speaker 1: the summer, I think it became pretty clear that there 348 00:18:29,400 --> 00:18:34,280 Speaker 1: were more severe problems with Lehman, and sitting on the 349 00:18:34,359 --> 00:18:38,719 Speaker 1: trading floor, we under I saw firsthand what our traders 350 00:18:38,800 --> 00:18:41,159 Speaker 1: were saying in the salesforce saying people didn't want us, 351 00:18:41,280 --> 00:18:43,480 Speaker 1: did not want Lehman as a counterparty, so we weren't 352 00:18:43,480 --> 00:18:46,520 Speaker 1: getting the trading flow. You were seeing serious issues in 353 00:18:46,640 --> 00:18:48,639 Speaker 1: terms of balance sheet as well. I think traders and 354 00:18:48,680 --> 00:18:51,480 Speaker 1: salesforce had an understanding that they were bigger issues. But 355 00:18:51,640 --> 00:18:55,680 Speaker 1: then again the backdrop was, well, who would let Lehman 356 00:18:55,760 --> 00:18:59,080 Speaker 1: go under? Lehman Brothers they would be a buyer. Bear 357 00:18:59,119 --> 00:19:00,919 Speaker 1: Stars went under, but their was a buyer, and there 358 00:19:01,000 --> 00:19:04,440 Speaker 1: was some there was a savior. Um. The likelihood that 359 00:19:04,520 --> 00:19:06,560 Speaker 1: Lehman would be able to fall into bankruptcy, I think 360 00:19:06,720 --> 00:19:10,760 Speaker 1: everybody up until last minute thought was a very low probability. UM. 361 00:19:10,960 --> 00:19:14,840 Speaker 1: It wasn't until that Sunday night, UM when it became 362 00:19:14,880 --> 00:19:17,840 Speaker 1: clear the Bank of America was buying Maryland, not Lehman Brothers, 363 00:19:18,600 --> 00:19:21,399 Speaker 1: Which weren't that fight for me in the end, but 364 00:19:21,800 --> 00:19:25,080 Speaker 1: at the time was absolute panic. It became clear that 365 00:19:25,160 --> 00:19:28,800 Speaker 1: we were indeed filing for bankruptcy, and I remember looking 366 00:19:28,920 --> 00:19:31,480 Speaker 1: watching TV and Singer, but you go to Lehman Brothers 367 00:19:31,480 --> 00:19:33,120 Speaker 1: to try to clear out their desks on the view 368 00:19:33,160 --> 00:19:35,359 Speaker 1: that maybe we'd be locked out on Monday morning. So, 369 00:19:35,680 --> 00:19:38,159 Speaker 1: you know, after several glasses of wine, my husband I 370 00:19:38,280 --> 00:19:41,680 Speaker 1: went over Leman to try to clear my my office 371 00:19:41,800 --> 00:19:44,639 Speaker 1: and everybody was on the trading floor and it was 372 00:19:44,840 --> 00:19:48,280 Speaker 1: just it was it was surreal. You know. The one thing, 373 00:19:48,600 --> 00:19:52,359 Speaker 1: the one little factoid about the Lehman story that I 374 00:19:52,600 --> 00:19:56,960 Speaker 1: think always surprises people was that Buffett had made a 375 00:19:57,520 --> 00:20:00,920 Speaker 1: offer that was ultimately rejected by dick Old, and that, 376 00:20:01,160 --> 00:20:03,920 Speaker 1: compared to what he ultimately ended up doing with Goldman Sachs, 377 00:20:04,680 --> 00:20:07,920 Speaker 1: was actually more generous offer. But at the time, the 378 00:20:08,000 --> 00:20:11,840 Speaker 1: assumption was Lehman isn't going away, He's trying to lower 379 00:20:11,920 --> 00:20:15,040 Speaker 1: ball us and steal the company, and you end up 380 00:20:15,080 --> 00:20:18,680 Speaker 1: in a situation that uh. I think the fact that 381 00:20:18,880 --> 00:20:22,280 Speaker 1: Fold never took that offer kind of made it hard 382 00:20:22,359 --> 00:20:25,080 Speaker 1: for the FED to come in and rescue them. You know, 383 00:20:25,160 --> 00:20:29,840 Speaker 1: there was rumors that um Paulson wasn't a fan of Folds, 384 00:20:29,880 --> 00:20:32,440 Speaker 1: and there was a little back and forth between the 385 00:20:32,480 --> 00:20:34,639 Speaker 1: two of them any truth to that or is that 386 00:20:34,800 --> 00:20:39,760 Speaker 1: just sort of I wouldn't know. I wouldn't know. I think, um, 387 00:20:41,080 --> 00:20:43,639 Speaker 1: that's the speculation. And I think that a lot of 388 00:20:43,680 --> 00:20:46,800 Speaker 1: people a Lehman believed that was the case. People at 389 00:20:46,920 --> 00:20:48,800 Speaker 1: Lehman Blood Green. I mean, there was a lot of 390 00:20:48,880 --> 00:20:55,080 Speaker 1: loyalty to right a long time, and you know, yes, 391 00:20:55,359 --> 00:20:57,840 Speaker 1: there was a there were there were excesses, there were problems, 392 00:20:57,960 --> 00:21:01,159 Speaker 1: there were a lot of mistakes made, but there were 393 00:21:01,160 --> 00:21:04,200 Speaker 1: a lot of great people there that were heavily committed 394 00:21:04,400 --> 00:21:06,879 Speaker 1: to the company, into the into the markets. So I 395 00:21:07,000 --> 00:21:09,520 Speaker 1: think that it was you know, it was really hard. 396 00:21:09,720 --> 00:21:10,879 Speaker 1: It was a really hard time for a lot I 397 00:21:10,920 --> 00:21:13,720 Speaker 1: could I can imagine. How do you know Jack Rivkin 398 00:21:13,920 --> 00:21:18,440 Speaker 1: very well because he ran Lehman Research back in the 399 00:21:19,200 --> 00:21:21,800 Speaker 1: eighties and nineties and did a really nice job of it. Yeah, 400 00:21:21,880 --> 00:21:25,479 Speaker 1: Lehman Research was number one and I i for years 401 00:21:25,720 --> 00:21:29,680 Speaker 1: it was very Robbie muto Um led research while I 402 00:21:29,800 --> 00:21:33,760 Speaker 1: was there, and he was incredibly dedicated, diligent. I mean, 403 00:21:34,000 --> 00:21:37,080 Speaker 1: the content coming out of Lehman Research was exceptional. Right, 404 00:21:37,200 --> 00:21:40,320 Speaker 1: That's the great tragedy of Lehman collapsing. It. You know, 405 00:21:40,359 --> 00:21:43,720 Speaker 1: who really cares about Dick full there was another twenty 406 00:21:43,800 --> 00:21:48,040 Speaker 1: thousand employees were so and a lot of them ended 407 00:21:48,119 --> 00:21:51,240 Speaker 1: up at Barklay's. Everybody did. That's what Barclay's what they bought, 408 00:21:51,280 --> 00:21:53,680 Speaker 1: the human capital, and they did well with him. Let's 409 00:21:53,760 --> 00:21:57,840 Speaker 1: talk a little bit about the current recovery and economic cycle. 410 00:21:57,960 --> 00:22:00,680 Speaker 1: Where where are we in the economy to die? Yeah, 411 00:22:00,720 --> 00:22:02,680 Speaker 1: I mean, it seems like this has been a pretty 412 00:22:03,080 --> 00:22:05,640 Speaker 1: old business cycle. So when you think about the number 413 00:22:05,680 --> 00:22:08,320 Speaker 1: of years we've theoretically been in recovery, it seems like 414 00:22:08,400 --> 00:22:10,920 Speaker 1: it's old. But in terms of the progress made, you 415 00:22:10,960 --> 00:22:13,440 Speaker 1: can still argue that it's fairly young. So when you 416 00:22:13,520 --> 00:22:18,120 Speaker 1: think about the cyclical sectors of the economy, housing is one, 417 00:22:18,280 --> 00:22:22,800 Speaker 1: consumer durables as another, capital expenditures another. We're still a 418 00:22:22,920 --> 00:22:25,240 Speaker 1: level as a share of the economy which are historically 419 00:22:25,280 --> 00:22:29,040 Speaker 1: low and arguably still close to recessionary territory. So I 420 00:22:29,200 --> 00:22:31,760 Speaker 1: think it is the case that there's room for growth, 421 00:22:31,840 --> 00:22:36,000 Speaker 1: there's room for expansion. There's been exceptional monetary policy support. 422 00:22:36,160 --> 00:22:39,520 Speaker 1: Monetary policy works with long lags um this environment of 423 00:22:39,680 --> 00:22:42,639 Speaker 1: very low rates and high liquidity ultimately should translate to 424 00:22:42,760 --> 00:22:46,080 Speaker 1: stronger economic growth. We mentioned earlier, your colleague Dave Rosenberg. 425 00:22:46,160 --> 00:22:48,919 Speaker 1: He's fond of showing the chart that shows the housing 426 00:22:49,000 --> 00:22:52,959 Speaker 1: recovery has bought home sales, both new and existing home 427 00:22:53,040 --> 00:22:57,400 Speaker 1: sales back to the levels where other recessions tend to bottom, 428 00:22:57,840 --> 00:22:59,600 Speaker 1: Like we're all the way up to the bottom of 429 00:22:59,640 --> 00:23:03,800 Speaker 1: preview is now. This was obviously a massive housing recession, 430 00:23:03,920 --> 00:23:06,320 Speaker 1: and that's where a lot of credit was, where a 431 00:23:06,359 --> 00:23:09,440 Speaker 1: lot of the crisis was centered. But when we talked 432 00:23:09,440 --> 00:23:14,000 Speaker 1: about housing recovery, why so weak, Why so soft despite 433 00:23:14,200 --> 00:23:17,479 Speaker 1: such fairy low low mortgage rates. And that's been one 434 00:23:17,480 --> 00:23:20,800 Speaker 1: of the puzzles. I think the challenge has been that 435 00:23:21,520 --> 00:23:24,560 Speaker 1: there was a lot of equity lost in the housing market, 436 00:23:24,760 --> 00:23:28,920 Speaker 1: so people have suffered severe home price declines UM, and 437 00:23:29,000 --> 00:23:31,480 Speaker 1: that held back some of the churn and the housing market. 438 00:23:31,520 --> 00:23:33,960 Speaker 1: You had to get back into positive equity UM. We 439 00:23:34,040 --> 00:23:37,800 Speaker 1: had to deal with an exceptional amount of foreclosures and 440 00:23:38,119 --> 00:23:40,760 Speaker 1: not quite ten million, but pretty close. Yeah, And that 441 00:23:40,920 --> 00:23:43,960 Speaker 1: created a lot of distressed inventory in the market that 442 00:23:44,040 --> 00:23:46,399 Speaker 1: had to clear and and luckily it cleared, and it 443 00:23:46,480 --> 00:23:49,960 Speaker 1: cleared in part because investors found opportunities in buying out 444 00:23:50,080 --> 00:23:52,879 Speaker 1: these distressed properties at deep discounts, some of which were 445 00:23:52,960 --> 00:23:56,399 Speaker 1: converted into rentals um and that's created a floor for 446 00:23:56,520 --> 00:23:58,919 Speaker 1: home prices. And now home prices have been recovering. They 447 00:23:58,920 --> 00:24:00,840 Speaker 1: start to turn in early two thousand and twelve, and 448 00:24:01,480 --> 00:24:04,119 Speaker 1: last year we're up about five percent. We're looking for 449 00:24:04,160 --> 00:24:06,280 Speaker 1: about three and a half percent appreciation this year. So 450 00:24:07,000 --> 00:24:10,679 Speaker 1: we've seen progress, but I still think that there's further upside. 451 00:24:10,720 --> 00:24:12,439 Speaker 1: And really where the upside is it's not so much 452 00:24:12,520 --> 00:24:15,479 Speaker 1: for home prices, but it's really for construction. I think 453 00:24:15,560 --> 00:24:17,920 Speaker 1: the level of our housing stock is too low to 454 00:24:18,000 --> 00:24:21,680 Speaker 1: accommodate the ultimate growth in householformation in the population, and 455 00:24:22,000 --> 00:24:24,679 Speaker 1: that's been very weak. We've had the story is millennials 456 00:24:24,720 --> 00:24:27,679 Speaker 1: living in their parents basement, but we're seeing signs now 457 00:24:27,760 --> 00:24:30,560 Speaker 1: that that's starting to turn. We are the most recent 458 00:24:30,640 --> 00:24:32,840 Speaker 1: data from the Census Bureau show that at the end 459 00:24:32,880 --> 00:24:35,600 Speaker 1: of last year there was a notable pickup in householfformation. 460 00:24:35,720 --> 00:24:38,399 Speaker 1: The data is extremely volatile, so you have to kind 461 00:24:38,440 --> 00:24:41,640 Speaker 1: of smooth through these quarterly swings. But for last year, 462 00:24:41,680 --> 00:24:44,760 Speaker 1: by my estimates, we created about eight hundred thousand households 463 00:24:46,800 --> 00:24:49,639 Speaker 1: normal one one to one to um if you have 464 00:24:49,800 --> 00:24:52,359 Speaker 1: normal headship rates. I think the good news is that 465 00:24:52,960 --> 00:24:55,359 Speaker 1: the millennial generation is a large cord the kids that 466 00:24:55,400 --> 00:24:57,520 Speaker 1: baby boomers, So there's a lot of them. And it 467 00:24:57,600 --> 00:25:00,240 Speaker 1: is to your point many who have been to laid 468 00:25:00,320 --> 00:25:02,800 Speaker 1: in entering the economy to a certain extent because of 469 00:25:03,440 --> 00:25:06,840 Speaker 1: the weakness in this business cycle, because of other challenges 470 00:25:06,920 --> 00:25:10,240 Speaker 1: related to student debt and as such. But over time, 471 00:25:10,840 --> 00:25:13,280 Speaker 1: these are going to be people who form households and 472 00:25:13,359 --> 00:25:15,640 Speaker 1: we need to build to accommodate it. What happens if 473 00:25:15,880 --> 00:25:18,160 Speaker 1: towards the latter part of this year, and I don't 474 00:25:18,200 --> 00:25:19,679 Speaker 1: want to guess if it's the summer or the end 475 00:25:19,720 --> 00:25:23,760 Speaker 1: of the year, maybe what happens to the housing market 476 00:25:23,840 --> 00:25:26,399 Speaker 1: if we see rates start to I don't even want 477 00:25:26,400 --> 00:25:29,680 Speaker 1: to say go up. Let's just say normalize, because this 478 00:25:29,840 --> 00:25:32,760 Speaker 1: is not a normal rate environment. If you could get 479 00:25:32,760 --> 00:25:35,560 Speaker 1: a thirty year fixed mortgage for three and a half percent, 480 00:25:36,200 --> 00:25:38,920 Speaker 1: that's pretty insane for what we've experienced for the past 481 00:25:40,520 --> 00:25:43,919 Speaker 1: forty years. There's nothing normal about this economy right now 482 00:25:44,560 --> 00:25:47,040 Speaker 1: or about the financial markets. I think there's been a 483 00:25:47,080 --> 00:25:50,000 Speaker 1: lot of distortions. So yeah, so let's say the Fed 484 00:25:50,080 --> 00:25:54,119 Speaker 1: starts hiking interest rates. There's liftoff, and there's that step 485 00:25:54,200 --> 00:25:57,680 Speaker 1: towards as you said, normalization, interest rates rise. I think 486 00:25:57,760 --> 00:26:00,639 Speaker 1: if it's you know, a reasonable increase is an interest rate, 487 00:26:00,640 --> 00:26:04,639 Speaker 1: it's a gradual rising percent a year might be a 488 00:26:04,720 --> 00:26:06,199 Speaker 1: little bit high. But if there's something a little bit 489 00:26:06,240 --> 00:26:08,119 Speaker 1: less than that, so it's even slower, the fet is 490 00:26:08,240 --> 00:26:11,560 Speaker 1: really gradual, and it's accompanied by stronger economic growth than 491 00:26:11,600 --> 00:26:13,520 Speaker 1: I think the housing market can handle it. If you 492 00:26:13,560 --> 00:26:16,520 Speaker 1: have something akin to the Taper tantrum, which was in 493 00:26:16,680 --> 00:26:20,040 Speaker 1: summer of two over a hundred basis point move higher 494 00:26:20,080 --> 00:26:22,600 Speaker 1: in interest rates in a two month time that shocked 495 00:26:22,760 --> 00:26:25,480 Speaker 1: the housing market, and that was clearly negative. If something 496 00:26:25,600 --> 00:26:28,080 Speaker 1: like that happened again, it would be a setback for 497 00:26:28,080 --> 00:26:29,960 Speaker 1: the housing market. What what do you think about the 498 00:26:30,119 --> 00:26:32,959 Speaker 1: theory that or the thesis have heard some people float 499 00:26:33,400 --> 00:26:36,640 Speaker 1: that as soon as the FETE starts raising rates, people 500 00:26:36,800 --> 00:26:39,639 Speaker 1: going to realize, hey, these really once in a generation 501 00:26:40,240 --> 00:26:42,440 Speaker 1: low rates are going away, and we better buy a 502 00:26:42,480 --> 00:26:44,800 Speaker 1: house now were we're gonna pay a lot more for 503 00:26:44,840 --> 00:26:48,280 Speaker 1: a mortgage. You know that there may be some initial 504 00:26:48,920 --> 00:26:52,720 Speaker 1: um move higher, maybe some generation of activity from that, 505 00:26:53,080 --> 00:26:56,000 Speaker 1: but I think it's quite temporary. Ultimately, what matters for 506 00:26:56,320 --> 00:27:01,040 Speaker 1: humbuying is income growth, not only today but also for tomorrow, 507 00:27:01,160 --> 00:27:04,600 Speaker 1: so expectations that income will remain positive and growing in 508 00:27:04,680 --> 00:27:07,760 Speaker 1: the years to come, and then affordability mortgage rates. But 509 00:27:07,880 --> 00:27:10,560 Speaker 1: I think probably the most important factors simply this idea 510 00:27:10,560 --> 00:27:13,240 Speaker 1: of job security. So the labor market is arguably the 511 00:27:13,280 --> 00:27:15,720 Speaker 1: most important thing. For housing, Let's put housing aside and 512 00:27:15,800 --> 00:27:18,879 Speaker 1: talk about some of your other favorite indicators. What do 513 00:27:18,920 --> 00:27:20,680 Speaker 1: you really like to look at that gives you a 514 00:27:20,760 --> 00:27:23,640 Speaker 1: sense of here's what's going on in the overall economy, 515 00:27:23,720 --> 00:27:27,040 Speaker 1: and here's what this means for equity. You're asking economists 516 00:27:27,080 --> 00:27:30,200 Speaker 1: for their favorite indicators. That's hard. Which child do you like? 517 00:27:31,960 --> 00:27:34,800 Speaker 1: I only have one child, that that's an easy question. 518 00:27:34,880 --> 00:27:36,879 Speaker 1: You're gonna end up having more than one kid, and 519 00:27:36,960 --> 00:27:38,800 Speaker 1: you're they're all going to ask you who do you like? 520 00:27:38,920 --> 00:27:42,879 Speaker 1: That have to lie to them and say I like you. So, so, 521 00:27:43,119 --> 00:27:46,600 Speaker 1: what is your favorite favorite indicator? Or let me rephrase it, 522 00:27:46,840 --> 00:27:49,200 Speaker 1: what do you think is the most interesting or perhaps 523 00:27:49,760 --> 00:27:52,879 Speaker 1: underrated indicator? Obviously, the jobs report every month is going 524 00:27:52,920 --> 00:27:54,680 Speaker 1: to get a lot of attention, and it is important 525 00:27:54,680 --> 00:27:56,000 Speaker 1: and you have to smooth through it, but we have 526 00:27:56,160 --> 00:27:58,520 Speaker 1: to look at it. It's it's relevant. I think retail 527 00:27:58,520 --> 00:28:02,719 Speaker 1: sales is an important indicator consumers makes up sevent GDP 528 00:28:02,960 --> 00:28:06,359 Speaker 1: and the consumer is faring I think is really an 529 00:28:06,440 --> 00:28:09,440 Speaker 1: important part of the overall story. It gives a sense 530 00:28:09,560 --> 00:28:11,879 Speaker 1: of what kind of future investment we might need, what 531 00:28:12,200 --> 00:28:14,040 Speaker 1: what kind of hiring are we actually seeing with the 532 00:28:14,119 --> 00:28:16,840 Speaker 1: quality of hiring. And what's been somewhat interesting to me 533 00:28:16,960 --> 00:28:19,679 Speaker 1: recently is the past three months consumer spending a retail 534 00:28:19,680 --> 00:28:23,320 Speaker 1: sales have been soft despite the dropping gasoline prices, this 535 00:28:23,600 --> 00:28:27,359 Speaker 1: despite the increase in income. Why do you think that is? 536 00:28:27,480 --> 00:28:30,000 Speaker 1: It's a puzzle. It could partly be that they're simply 537 00:28:30,080 --> 00:28:32,960 Speaker 1: a lag between the drop and gasoline prices and spending. 538 00:28:33,040 --> 00:28:35,680 Speaker 1: Consumers have to believe that it's a persistent drop in 539 00:28:35,760 --> 00:28:39,640 Speaker 1: gasoline prices and maybe can someum consumers are also saving 540 00:28:39,960 --> 00:28:43,080 Speaker 1: for bigger ticket items. So although when we see auto 541 00:28:43,160 --> 00:28:46,520 Speaker 1: sales other than this past month, which I think we 542 00:28:46,560 --> 00:28:48,760 Speaker 1: can all, I don't. I hate blaming stuff on the weather, 543 00:28:49,080 --> 00:28:52,360 Speaker 1: but it's been so good awful that I'm willing to 544 00:28:52,440 --> 00:28:54,720 Speaker 1: give them the benefits now. But we're still had a 545 00:28:54,760 --> 00:28:59,200 Speaker 1: sixteen million annual run rate. Those are huge numbers for automs, 546 00:28:59,280 --> 00:29:02,600 Speaker 1: but also in autos, unlike housing, you've had financing come 547 00:29:02,640 --> 00:29:05,120 Speaker 1: back and you've had financing come back pretty aggressively. So 548 00:29:05,160 --> 00:29:07,680 Speaker 1: the ability to get leveraged, the ability to spend again 549 00:29:07,760 --> 00:29:11,719 Speaker 1: for autos, which is something that I appreciated. You've seen, uh, 550 00:29:11,880 --> 00:29:14,440 Speaker 1: you know, a nice acceleration, and I actually think there's 551 00:29:14,480 --> 00:29:17,600 Speaker 1: sort of repside for auto sales. Really yeah, house information 552 00:29:17,680 --> 00:29:20,280 Speaker 1: is not even picked up yet, so we're seeing this 553 00:29:20,760 --> 00:29:24,200 Speaker 1: increase in autos even before you get the rebounded house information. 554 00:29:24,480 --> 00:29:27,520 Speaker 1: The gain of house information should also generate an increase 555 00:29:27,560 --> 00:29:30,840 Speaker 1: in demand for autos that's coming. So let's talk about 556 00:29:30,960 --> 00:29:34,920 Speaker 1: other durable goods. Um, we've seen it, seen this uptick 557 00:29:35,000 --> 00:29:37,840 Speaker 1: in autos, and you mentioned the credit situation, but we 558 00:29:37,920 --> 00:29:41,520 Speaker 1: haven't seen a giant uptick endurable goods, of which automobile 559 00:29:41,640 --> 00:29:45,400 Speaker 1: is just one. So what is it related to home sales? 560 00:29:45,480 --> 00:29:48,640 Speaker 1: Why are we not seeing washer dryers? You would think 561 00:29:48,680 --> 00:29:51,440 Speaker 1: people who can't move, all right, I'm stuck here. I 562 00:29:51,480 --> 00:29:52,800 Speaker 1: don't have a lot of equity in my house. I'm 563 00:29:52,840 --> 00:29:56,040 Speaker 1: not anywhere. Let's redo the kitchen or something to that effect. 564 00:29:56,360 --> 00:29:59,160 Speaker 1: Why have we not seen durable goods really tick up? 565 00:29:59,360 --> 00:30:02,400 Speaker 1: The way auto to have financing is one aspect, you know, 566 00:30:02,600 --> 00:30:05,200 Speaker 1: it's it's it's not as easy to get financing for 567 00:30:05,240 --> 00:30:07,200 Speaker 1: some of these other types of durable goods like appliances 568 00:30:07,240 --> 00:30:09,240 Speaker 1: and such. You can put you can take out a 569 00:30:09,480 --> 00:30:11,480 Speaker 1: you know, a revolving line on your credit card, but 570 00:30:11,680 --> 00:30:13,400 Speaker 1: the standards there are a little bit stricter than it 571 00:30:13,480 --> 00:30:15,720 Speaker 1: has been for autos. That's probably one a factor. I think. 572 00:30:15,800 --> 00:30:18,840 Speaker 1: The other one is that for for housing, yes, home 573 00:30:18,920 --> 00:30:21,320 Speaker 1: prices have recovered, but you still have a number of 574 00:30:21,520 --> 00:30:25,560 Speaker 1: homeowners that are either in you know, near negative equity 575 00:30:25,720 --> 00:30:28,600 Speaker 1: or kind of flat And it's also very hard to 576 00:30:28,720 --> 00:30:31,120 Speaker 1: extract money out of your house right now for these 577 00:30:31,160 --> 00:30:33,720 Speaker 1: types of renovation projects. So the ability to get to 578 00:30:33,760 --> 00:30:35,680 Speaker 1: do a cash out refinancing or the ability to get 579 00:30:35,720 --> 00:30:37,760 Speaker 1: a home equity line of credit, there's are much more 580 00:30:37,840 --> 00:30:40,640 Speaker 1: restricted than they had been in prior cycles. Well, as 581 00:30:40,720 --> 00:30:44,479 Speaker 1: we saw leading into the financial crisis, that framework reference 582 00:30:44,520 --> 00:30:47,120 Speaker 1: it was the easiest thing in the world. Now it's 583 00:30:47,160 --> 00:30:49,840 Speaker 1: not so much. It's the exact opposite. So if you 584 00:30:49,880 --> 00:30:53,480 Speaker 1: can't withdraw money from your house to renovate, you have 585 00:30:53,640 --> 00:30:55,440 Speaker 1: to have and it's hard to borrow. You have to 586 00:30:55,560 --> 00:30:58,720 Speaker 1: have cash upfront, and a lot of households are still 587 00:30:58,800 --> 00:31:01,520 Speaker 1: fairly budget constructed, not to get too personal about this, 588 00:31:01,640 --> 00:31:03,680 Speaker 1: but I tell the story all the time. So we 589 00:31:03,800 --> 00:31:07,360 Speaker 1: just moved in September. I recall doing a refinance and 590 00:31:07,440 --> 00:31:09,640 Speaker 1: I want to say oh six or oh seven, where 591 00:31:09,680 --> 00:31:12,080 Speaker 1: the guy literally pulled up to our driveway, flung the 592 00:31:12,120 --> 00:31:15,040 Speaker 1: door open, left the car running, came in with papers 593 00:31:15,160 --> 00:31:17,600 Speaker 1: and apologized, Hey, I have a clothing to go to 594 00:31:17,680 --> 00:31:20,480 Speaker 1: im late, sign here here, initial here, and gave us 595 00:31:20,520 --> 00:31:22,680 Speaker 1: a check and he ran out the door. My wife 596 00:31:22,720 --> 00:31:24,760 Speaker 1: and I looked at each other like, did that really happen? 597 00:31:25,200 --> 00:31:27,560 Speaker 1: We're sitting here with the thirty check and our our 598 00:31:27,600 --> 00:31:30,040 Speaker 1: mortgage payments are five hundred dollars less a month, and 599 00:31:30,120 --> 00:31:33,000 Speaker 1: this guy was a ghost, was in and out. Now, 600 00:31:33,520 --> 00:31:36,800 Speaker 1: we just moved in September. It was the most insane 601 00:31:36,960 --> 00:31:41,240 Speaker 1: set of experiences. That was no stone left. It was 602 00:31:41,400 --> 00:31:45,720 Speaker 1: as opposite as anything you can imagine. I'm wondering how 603 00:31:46,000 --> 00:31:50,840 Speaker 1: significant that is relative to what we're seeing in housing, 604 00:31:50,880 --> 00:31:53,320 Speaker 1: what we're seeing endurable goods, and we're not seeing that 605 00:31:53,480 --> 00:31:56,720 Speaker 1: in autos. And maybe that's why. Yeah, I think listen. 606 00:31:56,840 --> 00:32:00,680 Speaker 1: Credit is the it's a fuel for the anomic engine. 607 00:32:00,800 --> 00:32:03,400 Speaker 1: And if credit is tight, which it is now for 608 00:32:03,480 --> 00:32:07,680 Speaker 1: our mortgages, it will limit the pace of activity. Um, 609 00:32:07,800 --> 00:32:10,160 Speaker 1: and you have seen the pendulum swing to the extreme 610 00:32:10,240 --> 00:32:13,520 Speaker 1: from a very easy market to one that's quite tight. Um. 611 00:32:13,640 --> 00:32:16,400 Speaker 1: And maybe it has been a you know, excessive move, 612 00:32:16,560 --> 00:32:18,400 Speaker 1: but there were a lot of changes that had to 613 00:32:18,440 --> 00:32:21,640 Speaker 1: be made and UM, that process has been painful. We've 614 00:32:21,640 --> 00:32:24,720 Speaker 1: been speaking with Michelle Meyer. She is the deputy chief 615 00:32:24,760 --> 00:32:28,520 Speaker 1: economist for North America for Bank America Merrill Lynch. If 616 00:32:28,600 --> 00:32:31,360 Speaker 1: you've enjoyed this conversation, be shure in here the rest 617 00:32:31,440 --> 00:32:34,720 Speaker 1: of it. You can find that podcast either at Apple 618 00:32:34,840 --> 00:32:39,720 Speaker 1: iTunes or on Bloomberg dot com. Check out my Twitter 619 00:32:39,840 --> 00:32:43,280 Speaker 1: feed at rid Holts or my daily column on Bloomberg 620 00:32:43,400 --> 00:32:46,880 Speaker 1: View dot com. I'm Barry Ridhults. You're listening to Masters 621 00:32:46,920 --> 00:32:55,520 Speaker 1: in Business on Bloomberg Radio. Hi, welcome back to the show. 622 00:32:55,760 --> 00:32:59,120 Speaker 1: This is our podcast portion, which you know already because 623 00:32:59,160 --> 00:33:01,680 Speaker 1: if you're hearing this, you're not listening to the radio. 624 00:33:01,800 --> 00:33:05,600 Speaker 1: You're listening either to an MP three or Apple iTunes 625 00:33:05,760 --> 00:33:08,520 Speaker 1: or SoundCloud or something like that. My guest today is 626 00:33:08,600 --> 00:33:11,640 Speaker 1: Michelle Myers. I know Michelle god I think I first 627 00:33:11,680 --> 00:33:14,840 Speaker 1: met you with Dave Rosenberg so many many years ago, 628 00:33:15,360 --> 00:33:18,280 Speaker 1: and you've come to some of the um. You know, 629 00:33:18,360 --> 00:33:23,320 Speaker 1: Scarsdale Equities started something many decades ago if you read 630 00:33:23,440 --> 00:33:27,240 Speaker 1: the book The Money Game by Adam Smith. Not that 631 00:33:27,320 --> 00:33:30,040 Speaker 1: Adam Smith, it's just the nom de PLUMEA. They talked 632 00:33:30,040 --> 00:33:33,680 Speaker 1: about these idea lunches and I got fortunate enough to 633 00:33:33,720 --> 00:33:36,680 Speaker 1: be invited to one some years ago, and I said, 634 00:33:36,760 --> 00:33:38,560 Speaker 1: these are great, but I got work to do during 635 00:33:38,560 --> 00:33:41,200 Speaker 1: the day. Why don't we make these idea dinners. And 636 00:33:41,320 --> 00:33:44,040 Speaker 1: they said, no, we we're gonna stick with lunches. So 637 00:33:44,680 --> 00:33:46,880 Speaker 1: we started doing our own sort of dinners. And you've 638 00:33:46,960 --> 00:33:49,080 Speaker 1: come to a few of these. I think one of 639 00:33:49,120 --> 00:33:52,560 Speaker 1: the questions I have for you, um, was who were 640 00:33:52,640 --> 00:33:55,840 Speaker 1: some of your economist heroes you'd like to meet? And 641 00:33:56,000 --> 00:34:00,160 Speaker 1: you finally managed to meet um Paul Krugman at one 642 00:34:00,200 --> 00:34:03,840 Speaker 1: of these dinners. Yeah, he is one of the economist seers. 643 00:34:03,880 --> 00:34:09,080 Speaker 1: I just find him to be exceptionally smart, which is 644 00:34:09,200 --> 00:34:11,560 Speaker 1: not a bold statement given that he is a noble 645 00:34:12,960 --> 00:34:16,040 Speaker 1: not giving him out to it pretty much that that's 646 00:34:16,120 --> 00:34:20,720 Speaker 1: one of the qualifications, not stupid, not stupid. So clearly 647 00:34:21,200 --> 00:34:25,040 Speaker 1: he's an incredibly smart economist. But he is really passionate too, 648 00:34:25,080 --> 00:34:27,680 Speaker 1: And whether or not you agree with his political stance. 649 00:34:28,160 --> 00:34:30,920 Speaker 1: I think his his passion and his ability to lay 650 00:34:30,960 --> 00:34:35,680 Speaker 1: out a concise, interesting argument is is fascinating. So I 651 00:34:36,000 --> 00:34:39,440 Speaker 1: read him regularly. I really enjoy his blog. The page 652 00:34:39,680 --> 00:34:43,400 Speaker 1: that So he's a Monday Friday UM writer for the 653 00:34:43,440 --> 00:34:45,680 Speaker 1: New York Times, but then he has a blog and 654 00:34:45,920 --> 00:34:48,360 Speaker 1: then is conscious of a liberal is blocked. But that 655 00:34:48,600 --> 00:34:53,160 Speaker 1: real estate that he owns on Mondays and Fridays. Some 656 00:34:53,360 --> 00:34:58,440 Speaker 1: people have called that the most influential commentary quote unquote 657 00:34:58,480 --> 00:35:01,600 Speaker 1: real estate in the world old of publishing. That that 658 00:35:01,840 --> 00:35:05,120 Speaker 1: is an amazing page. He says things that and he 659 00:35:05,200 --> 00:35:09,000 Speaker 1: says in a way that other people won't say, and 660 00:35:09,120 --> 00:35:11,640 Speaker 1: and and and sometimes he's sometimes he's wrong, but a 661 00:35:11,760 --> 00:35:13,719 Speaker 1: lot of time he is right. And he's saying things 662 00:35:13,760 --> 00:35:15,160 Speaker 1: that other people are thinking but they're not willing to 663 00:35:15,160 --> 00:35:17,520 Speaker 1: put on paper. I've disagreed with him a couple of times. 664 00:35:17,560 --> 00:35:20,600 Speaker 1: He and I disagree about securitization. You know, he doesn't 665 00:35:20,640 --> 00:35:22,440 Speaker 1: like it. I say, well, if you have garbage in, 666 00:35:22,640 --> 00:35:26,120 Speaker 1: garbage out, um, but as long as you're not feeding 667 00:35:26,400 --> 00:35:29,360 Speaker 1: bad sausage into bad meat into the machine, you're not 668 00:35:29,440 --> 00:35:32,239 Speaker 1: going to get bad sausage. And what we did during 669 00:35:32,280 --> 00:35:34,960 Speaker 1: the crisis is all those bad mortgages went in and 670 00:35:35,040 --> 00:35:37,480 Speaker 1: guess what came out the end. So it's it's not 671 00:35:37,600 --> 00:35:40,799 Speaker 1: the machinery, it's it's it's the food stuff you're you're 672 00:35:40,840 --> 00:35:46,120 Speaker 1: putting in. What what other rockstar economists impress you? Oh? Um, 673 00:35:48,640 --> 00:35:51,879 Speaker 1: rock star? What is the rock star? Well? Krugman is one. 674 00:35:52,440 --> 00:35:56,359 Speaker 1: Who else is a rock star economist? Um? I would say, 675 00:35:57,320 --> 00:35:59,279 Speaker 1: I don't know if people still think this of Ryan 676 00:35:59,360 --> 00:36:02,759 Speaker 1: Hart and rogue office rock star economists. And then we 677 00:36:02,920 --> 00:36:07,480 Speaker 1: have guys like um Neurio Rubini, who I think maybe 678 00:36:07,760 --> 00:36:10,959 Speaker 1: uh peaked a few years ago, but was highly holly 679 00:36:11,080 --> 00:36:15,040 Speaker 1: regarded by a little a little too much. UM. The 680 00:36:15,160 --> 00:36:20,520 Speaker 1: person who proceeded Dave Rosenberg was Gary Schilling, who's still 681 00:36:20,719 --> 00:36:24,200 Speaker 1: publishing on a regular basis, and another one who says 682 00:36:24,360 --> 00:36:26,960 Speaker 1: kind of outrageous things that have turned out to be 683 00:36:27,080 --> 00:36:30,799 Speaker 1: more right than wrong. He's been pounding the table about hey, 684 00:36:30,920 --> 00:36:32,920 Speaker 1: the ten years going to have a one handle on 685 00:36:33,040 --> 00:36:36,920 Speaker 1: it before you can imagine? Why are the rock stars negative? Um, 686 00:36:38,280 --> 00:36:41,360 Speaker 1: let's say Justin Wolfer's up and coming. Probably not. I 687 00:36:41,360 --> 00:36:45,120 Speaker 1: wouldn't describe him as a as a negative. His wife 688 00:36:45,200 --> 00:36:48,320 Speaker 1: I think UM ended up on was it the c 689 00:36:48,520 --> 00:36:52,480 Speaker 1: e A or where did where did she end up going? Um, well, 690 00:36:53,239 --> 00:36:55,879 Speaker 1: let's not use the term rock star. What other economists 691 00:36:56,400 --> 00:37:02,080 Speaker 1: do you find influential or especially admire? Reinhardt and rogue 692 00:37:02,080 --> 00:37:06,120 Speaker 1: Off I think was particularly influential in this cycle because 693 00:37:06,239 --> 00:37:12,320 Speaker 1: what they their work was around how do economies cope 694 00:37:12,400 --> 00:37:15,320 Speaker 1: and how do they deal with financial crisis and balance 695 00:37:15,360 --> 00:37:19,120 Speaker 1: sheet recessions? So their work I think really rang true 696 00:37:19,280 --> 00:37:22,239 Speaker 1: and mattered a great deal um this time around. So 697 00:37:22,320 --> 00:37:24,400 Speaker 1: there are a lot of lessons learned from there. People 698 00:37:24,440 --> 00:37:27,960 Speaker 1: obsess about the Excel error. But but if you go 699 00:37:28,120 --> 00:37:30,839 Speaker 1: back and look at and I'm getting the dates right, 700 00:37:31,360 --> 00:37:34,719 Speaker 1: I want to say January two eight they had a 701 00:37:34,800 --> 00:37:39,440 Speaker 1: paper called looking at five Financial Crises January o eight, 702 00:37:39,600 --> 00:37:44,200 Speaker 1: But forget Lehman before Bear Starns, and that they basically said, hey, 703 00:37:44,280 --> 00:37:48,040 Speaker 1: the typical financial crisis see stock markets cut in half 704 00:37:48,120 --> 00:37:52,080 Speaker 1: and real estate drop thirty and it looks like we're 705 00:37:52,120 --> 00:37:54,640 Speaker 1: heading into that sort of a credit crisis that could 706 00:37:54,640 --> 00:37:57,840 Speaker 1: result in that nobody really paid attend. I happen to 707 00:37:57,880 --> 00:38:02,360 Speaker 1: see that paper and said, wow, this is astonishingly data driven, 708 00:38:02,480 --> 00:38:06,160 Speaker 1: and that basically paper became the basis of years of 709 00:38:06,239 --> 00:38:08,879 Speaker 1: financial following this. This Time Is Different was their book, 710 00:38:09,200 --> 00:38:12,440 Speaker 1: but which is a difficult book to get through. But um, 711 00:38:12,760 --> 00:38:16,320 Speaker 1: here's another rock star. Colomists and Robert Schiller. Love Schiller, 712 00:38:16,680 --> 00:38:19,960 Speaker 1: absolutely had Schiller. We had him in here a few 713 00:38:20,040 --> 00:38:23,800 Speaker 1: months ago. The nicest guy in the world and just 714 00:38:24,719 --> 00:38:28,560 Speaker 1: so insightful and so he's just delightful. Have you ever 715 00:38:28,600 --> 00:38:30,239 Speaker 1: had a chance to work with him in any I've 716 00:38:30,320 --> 00:38:33,239 Speaker 1: met him as well. Um So I got to shake 717 00:38:33,320 --> 00:38:35,920 Speaker 1: his hand and talked to him a bit and another 718 00:38:35,960 --> 00:38:41,000 Speaker 1: Nobel laureate. Yeah, um and he his clearly rational exuberance. 719 00:38:41,360 --> 00:38:43,520 Speaker 1: Um that went a long way. And he's had great 720 00:38:43,560 --> 00:38:45,920 Speaker 1: calls both on the stock market around the tech bus 721 00:38:46,040 --> 00:38:48,680 Speaker 1: and the housing market around the housing bust. Um. But 722 00:38:48,920 --> 00:38:52,400 Speaker 1: his analysis is way of thinking. Um, I think it 723 00:38:52,880 --> 00:38:56,680 Speaker 1: it's you know, it's extraordinarily high quality and it's it's 724 00:38:57,200 --> 00:39:00,320 Speaker 1: it's very interesting. Um So, yeah, that he would be 725 00:39:00,400 --> 00:39:03,040 Speaker 1: high up on my list. So let me shift gears 726 00:39:03,080 --> 00:39:05,000 Speaker 1: a little bit on you. What do you think the 727 00:39:05,160 --> 00:39:09,400 Speaker 1: role of the economist is on Wall Street? What is 728 00:39:09,480 --> 00:39:11,440 Speaker 1: the role of the economists on Wall Street? That's a 729 00:39:11,480 --> 00:39:15,160 Speaker 1: great question, um So, I think the way I interpret 730 00:39:15,360 --> 00:39:17,720 Speaker 1: the role is that you're supposed to be a source 731 00:39:17,800 --> 00:39:22,440 Speaker 1: of information to the salesforce, to our traders, so internally 732 00:39:22,600 --> 00:39:26,960 Speaker 1: but also externally to our clients. So that means analyzing 733 00:39:27,040 --> 00:39:29,800 Speaker 1: the high frequency data as it comes in. What is 734 00:39:29,880 --> 00:39:33,719 Speaker 1: our expectation for the data, where is it relative to consensus, 735 00:39:33,840 --> 00:39:35,839 Speaker 1: what can go wrong? How do we interpret it once 736 00:39:35,880 --> 00:39:38,560 Speaker 1: it comes out? Where are the special factors? So have 737 00:39:38,840 --> 00:39:42,680 Speaker 1: real time, fast analysis on the high frequency data, but 738 00:39:42,719 --> 00:39:45,400 Speaker 1: then also be able to paint a picture for the 739 00:39:45,480 --> 00:39:48,560 Speaker 1: economic account for the economy in the medium term, and 740 00:39:48,640 --> 00:39:50,640 Speaker 1: some of the risks seem into the longer term. So 741 00:39:50,719 --> 00:39:52,880 Speaker 1: you have to be able to remove yourself from the 742 00:39:52,960 --> 00:39:55,560 Speaker 1: day to day volatility and the data and in the 743 00:39:55,600 --> 00:39:58,120 Speaker 1: day to day volatility in the markets and say what 744 00:39:58,239 --> 00:40:01,520 Speaker 1: are we really learn ing? What what do we really 745 00:40:01,640 --> 00:40:04,719 Speaker 1: know about the economy, and what is our baseline forecasts? 746 00:40:04,760 --> 00:40:07,480 Speaker 1: And there were the risks around that forecast because I 747 00:40:07,560 --> 00:40:09,480 Speaker 1: think when you're in the markets and you're in front 748 00:40:09,520 --> 00:40:12,000 Speaker 1: of a screen day after day, it's really hard not 749 00:40:12,160 --> 00:40:14,239 Speaker 1: to get influenced by what the market is telling us 750 00:40:14,520 --> 00:40:17,720 Speaker 1: today in terms of what will mean for tomorrow. Timing 751 00:40:17,800 --> 00:40:20,680 Speaker 1: and understanding identifying turning points is very hard to do. 752 00:40:21,160 --> 00:40:23,360 Speaker 1: But to the extent that we can help with that. 753 00:40:23,440 --> 00:40:25,920 Speaker 1: As an economist, I think that's that's an important part. 754 00:40:26,200 --> 00:40:29,839 Speaker 1: So you raise a really interesting issue, is the relationship 755 00:40:29,960 --> 00:40:34,480 Speaker 1: of markets to the economy. How fast do the markets 756 00:40:34,640 --> 00:40:37,960 Speaker 1: turn before we start seeing it in the economic data, 757 00:40:38,400 --> 00:40:41,879 Speaker 1: either up off the lows or down off the off 758 00:40:41,920 --> 00:40:45,600 Speaker 1: the highs. What's the lag like and why why is 759 00:40:45,680 --> 00:40:50,680 Speaker 1: it such a sizeable time period? Yeah, I mean, I think, um, 760 00:40:50,960 --> 00:40:53,879 Speaker 1: so anything with the markets. That's for equity markets. Um, 761 00:40:54,840 --> 00:40:59,200 Speaker 1: they're capturing the health of the major corporations in the country. 762 00:40:59,719 --> 00:41:04,719 Speaker 1: So um, if investors are starting to see problems in 763 00:41:04,760 --> 00:41:10,520 Speaker 1: these corporations, revenue, earnings misses, things that are essentially suggesting, hey, 764 00:41:10,600 --> 00:41:13,840 Speaker 1: this economy isn't anyone all cylinders anymore. That's going to 765 00:41:13,920 --> 00:41:16,440 Speaker 1: show up in the market before we'll see it in 766 00:41:16,520 --> 00:41:19,320 Speaker 1: the economic data. Yeah, to a certain extent. Now, of course, 767 00:41:19,640 --> 00:41:21,400 Speaker 1: how companies are doing a not just a function of 768 00:41:21,440 --> 00:41:23,400 Speaker 1: their revenues and their sales. It's so so a function 769 00:41:23,480 --> 00:41:26,600 Speaker 1: of just their profitability, so their cost cutting. So you 770 00:41:26,680 --> 00:41:30,160 Speaker 1: can have situations where you have really high corporate profits 771 00:41:30,200 --> 00:41:31,680 Speaker 1: like in this ycle. For a period of time it 772 00:41:31,800 --> 00:41:35,000 Speaker 1: was a profits recovery because of the excessive cost cutting, 773 00:41:35,080 --> 00:41:39,560 Speaker 1: but you weren't really seeing underlying economic growth. So there's disconnects. Um. 774 00:41:40,120 --> 00:41:42,680 Speaker 1: But because the fact that the equity markets are capturing 775 00:41:42,800 --> 00:41:44,759 Speaker 1: large corporations, it's going to be indicative of what the 776 00:41:44,800 --> 00:41:47,120 Speaker 1: economy is saying. And then I think in terms of 777 00:41:47,120 --> 00:41:51,399 Speaker 1: the fixed income markets, in terms of relay treasuries move um, 778 00:41:52,480 --> 00:41:56,759 Speaker 1: that's very much driven by expectations for Fed policy. And 779 00:41:56,880 --> 00:42:00,360 Speaker 1: one of the interesting observations today is that the market 780 00:42:00,480 --> 00:42:04,880 Speaker 1: is pricing in an extraordinarily low path of the terminal 781 00:42:04,960 --> 00:42:07,440 Speaker 1: Fed funds rates. So they're saying that the Fed, yeah, 782 00:42:07,480 --> 00:42:09,640 Speaker 1: they may start hiking interest rates before the end of 783 00:42:09,680 --> 00:42:11,560 Speaker 1: the year, but they're not going to accomplish that much. 784 00:42:11,560 --> 00:42:16,439 Speaker 1: They're not going to get very far. Um. Oh god, 785 00:42:16,480 --> 00:42:18,560 Speaker 1: that would be dismal. But no, you know, maybe a 786 00:42:18,680 --> 00:42:21,040 Speaker 1: terminal rate two and a half percent or so. But 787 00:42:21,200 --> 00:42:23,160 Speaker 1: think about two and a half percent Fed funds right 788 00:42:23,239 --> 00:42:26,960 Speaker 1: historically very low, very sominating, incredibly low. It's incredible comedy. 789 00:42:27,000 --> 00:42:28,480 Speaker 1: So if all the FED is able to achieve is 790 00:42:28,520 --> 00:42:29,920 Speaker 1: to get the Fed funds right up to two and 791 00:42:29,920 --> 00:42:33,000 Speaker 1: a half percent, then it means that there's something much 792 00:42:33,080 --> 00:42:35,600 Speaker 1: weaker about the economy, and that the economy can't handle 793 00:42:35,680 --> 00:42:37,680 Speaker 1: higher interest rates, and that's what the market is telling us. 794 00:42:37,920 --> 00:42:39,640 Speaker 1: The FED is not saying that. If you look at 795 00:42:39,680 --> 00:42:43,319 Speaker 1: what the FED is projecting in their Summary of Economic projections, 796 00:42:43,719 --> 00:42:45,600 Speaker 1: they say they can get interest rates to three and 797 00:42:45,600 --> 00:42:49,120 Speaker 1: a half or three and a quarter, but but over 798 00:42:49,280 --> 00:42:54,000 Speaker 1: gradual long period of time. Not okay, so that's two years. 799 00:42:54,080 --> 00:42:58,480 Speaker 1: So let's let's take the counter argument that we have 800 00:42:58,560 --> 00:43:03,160 Speaker 1: a distortion in interest rates because of QUEI and the 801 00:43:03,280 --> 00:43:07,520 Speaker 1: purchase of bonds. And when you look at quality a 802 00:43:07,760 --> 00:43:11,719 Speaker 1: rated sovereign debt, there really isn't all that much of it. 803 00:43:11,800 --> 00:43:15,239 Speaker 1: I know, we talked about deficits and all these other things, 804 00:43:15,360 --> 00:43:18,839 Speaker 1: but when you look around the world, how much high 805 00:43:19,000 --> 00:43:21,719 Speaker 1: quality sovereign paper is there? And keep in mind, we 806 00:43:21,840 --> 00:43:26,040 Speaker 1: have this huge demographic that's aging, whose portfolios are becoming 807 00:43:26,120 --> 00:43:29,600 Speaker 1: more and more bonds heavy. They're big buyers of this. 808 00:43:29,800 --> 00:43:32,640 Speaker 1: We have lots of foundations. Is a tremor. I don't 809 00:43:32,640 --> 00:43:35,240 Speaker 1: have to tell you this tremendous amount of wealth around 810 00:43:35,280 --> 00:43:40,600 Speaker 1: the world. Very often that's a fairly conservative portfolio fifty 811 00:43:40,680 --> 00:43:44,360 Speaker 1: fifty or sixty forty, not as heavy equities as you 812 00:43:45,200 --> 00:43:48,759 Speaker 1: might be typical of a twentysomething. Is it possible that 813 00:43:49,800 --> 00:43:54,839 Speaker 1: what we're seeing is a shortage of quality sovereign paper, Well, 814 00:43:54,880 --> 00:43:57,880 Speaker 1: it seems to be. UM certainly one of the themes 815 00:43:57,920 --> 00:44:01,479 Speaker 1: of last year's everybody was expecting the tenure to head higher. 816 00:44:01,680 --> 00:44:04,080 Speaker 1: We can get to above three percent. That was very 817 00:44:04,160 --> 00:44:07,040 Speaker 1: much the consensus view. In the exact opposite have happened. 818 00:44:07,160 --> 00:44:11,480 Speaker 1: We got to a one handle briefly, um so. And 819 00:44:11,800 --> 00:44:14,680 Speaker 1: I think one of the factors that we have probably 820 00:44:14,880 --> 00:44:17,279 Speaker 1: was underappreciated is what you just said, that there was 821 00:44:17,840 --> 00:44:21,800 Speaker 1: a search um for yields and for quality assets, and 822 00:44:22,280 --> 00:44:26,920 Speaker 1: with so much UM liquidity from central banks, it forced 823 00:44:26,960 --> 00:44:31,399 Speaker 1: investors to, you know, move into U s treasuries because 824 00:44:31,400 --> 00:44:33,719 Speaker 1: if you think about the yield and US treasuries versus 825 00:44:33,840 --> 00:44:37,960 Speaker 1: let's say, German bonds, it's more attractive to buy US treasuries. 826 00:44:38,120 --> 00:44:41,239 Speaker 1: And and you know, does anyone really think the US 827 00:44:41,320 --> 00:44:44,640 Speaker 1: is going to default on its treasuries to the point 828 00:44:44,760 --> 00:44:46,680 Speaker 1: that it were worth a point in a quarter more 829 00:44:46,840 --> 00:44:50,600 Speaker 1: than than the German bonds or the Swiss bonds it's 830 00:44:50,840 --> 00:44:55,160 Speaker 1: or or the Japanese bonds. It's really quite an astonishing disparity. 831 00:44:55,520 --> 00:44:57,920 Speaker 1: There is there is and um That's why when you 832 00:44:57,960 --> 00:45:01,520 Speaker 1: think about going back to this idea of the markets distorted, 833 00:45:01,640 --> 00:45:04,600 Speaker 1: and how do you really understand the signal coming out 834 00:45:04,600 --> 00:45:07,399 Speaker 1: of the markets. There's a question about that because we've 835 00:45:07,480 --> 00:45:12,040 Speaker 1: never had such accommodative monetary policy, not just from the 836 00:45:12,080 --> 00:45:14,759 Speaker 1: Federal Reserve but globally. So let's talk a little bit 837 00:45:14,760 --> 00:45:19,080 Speaker 1: about Quei and Zurup and monetary policy here in the 838 00:45:19,280 --> 00:45:22,080 Speaker 1: US with the Federal Reserve and the e c B 839 00:45:22,239 --> 00:45:25,920 Speaker 1: in Europe and the Bank of Japan. What is the 840 00:45:26,040 --> 00:45:30,600 Speaker 1: impact of all this monetary policy trying to stimulate the 841 00:45:30,680 --> 00:45:38,560 Speaker 1: economy um in light of somewhat missing fiscal stimulus. Certainly 842 00:45:38,600 --> 00:45:42,000 Speaker 1: in Europe, their austerity is there's been no fiscal stimulus. 843 00:45:42,400 --> 00:45:44,960 Speaker 1: They finally started some of that in Japan, and I've 844 00:45:45,000 --> 00:45:47,759 Speaker 1: seen somewhat of a reaction, and in the US we 845 00:45:47,880 --> 00:45:50,880 Speaker 1: haven't really seen a whole whole lot of compared to 846 00:45:51,000 --> 00:45:55,080 Speaker 1: pass cycles, this seems to be a fairly muted fiscal response, 847 00:45:55,200 --> 00:45:59,920 Speaker 1: but an unusually robust monetary response. Yeah, I mean, I think, 848 00:46:00,120 --> 00:46:02,279 Speaker 1: you know, it seems like the crisis was a long 849 00:46:02,360 --> 00:46:05,279 Speaker 1: time ago at this point, and it was, but the 850 00:46:05,400 --> 00:46:11,320 Speaker 1: initial um response after the crisis was extraordinary. On the 851 00:46:11,400 --> 00:46:13,719 Speaker 1: fiscal side as well. Let me think about the a 852 00:46:14,000 --> 00:46:16,960 Speaker 1: r A. The American Recovering Investment Act was a massive 853 00:46:16,960 --> 00:46:19,919 Speaker 1: amount of eight hundred billion dollars, two thirds of which 854 00:46:20,000 --> 00:46:24,320 Speaker 1: were temporary tax cuts and extension of of unemployment insurance. 855 00:46:24,719 --> 00:46:30,480 Speaker 1: Not quite a trillion dollars your he wanted three. Yeah, 856 00:46:31,320 --> 00:46:35,440 Speaker 1: he criticizes that it wasn't enough, it wasn't enough stimulus, 857 00:46:35,480 --> 00:46:37,800 Speaker 1: and maybe it maybe it wasn't, but who knows what 858 00:46:37,880 --> 00:46:40,520 Speaker 1: the counter factual was, but it was it was a 859 00:46:41,200 --> 00:46:46,280 Speaker 1: you know, an aggressive response to an extraordinary recession, certainly 860 00:46:46,320 --> 00:46:48,600 Speaker 1: more aggressive than we saw in Europe. They went the 861 00:46:48,680 --> 00:46:52,640 Speaker 1: opposite direction. Here's your counterfactual is here's what happens. That's 862 00:46:52,640 --> 00:46:55,040 Speaker 1: a counterfactual to the other way. Here's what happens. If 863 00:46:55,080 --> 00:46:57,520 Speaker 1: we don't put a trillion dollars worth of stimulus in, 864 00:46:58,239 --> 00:47:01,399 Speaker 1: you end up with a five year long recession. Like yeah. 865 00:47:01,480 --> 00:47:03,959 Speaker 1: So now the question is, and this is a question 866 00:47:04,040 --> 00:47:06,520 Speaker 1: always for policy makers, and this is where I think, again, 867 00:47:06,600 --> 00:47:09,600 Speaker 1: going back to Krugman's arguments, there's a lot of pushback, 868 00:47:09,719 --> 00:47:14,160 Speaker 1: which is, policymakers are designed to smooth the business cycle, 869 00:47:14,200 --> 00:47:16,320 Speaker 1: and certainly a federal reserve is you're not supposed to 870 00:47:16,320 --> 00:47:18,720 Speaker 1: allow the economy to overheating it all out. Now, suppose 871 00:47:18,760 --> 00:47:21,839 Speaker 1: allowed the economy to uh to to fall into two 872 00:47:21,920 --> 00:47:25,040 Speaker 1: deeper recessions, so you smooth the cycle. But the question 873 00:47:25,200 --> 00:47:28,600 Speaker 1: is what is what is what is the best approach? 874 00:47:29,320 --> 00:47:31,960 Speaker 1: Is it better to just not have a policy response, 875 00:47:32,000 --> 00:47:34,879 Speaker 1: to have a very deep recession, but allow for there 876 00:47:34,920 --> 00:47:37,480 Speaker 1: to be natural clearing and then you have a very 877 00:47:38,080 --> 00:47:42,480 Speaker 1: rapid and robust recovery after a period of severe pain. Um. 878 00:47:42,560 --> 00:47:46,360 Speaker 1: And that's where there's a debate between free market views 879 00:47:46,719 --> 00:47:50,200 Speaker 1: versus those that have more Keynesian and believe that there 880 00:47:50,200 --> 00:47:54,120 Speaker 1: should be a policy response. And I think broadly speaking, 881 00:47:54,440 --> 00:47:57,920 Speaker 1: the Kinesian views have one out in this scenario in 882 00:47:57,960 --> 00:48:01,880 Speaker 1: this way, um. But history will tell us after the 883 00:48:01,960 --> 00:48:04,719 Speaker 1: fact which was really right. The other issue we run 884 00:48:04,800 --> 00:48:07,640 Speaker 1: into when trying to look at that natural experiment between 885 00:48:07,640 --> 00:48:11,560 Speaker 1: the US and Europe is that the electorate only tolerates 886 00:48:11,600 --> 00:48:14,040 Speaker 1: so much pain, and so in a lot of these 887 00:48:14,120 --> 00:48:17,879 Speaker 1: countries in Europe where you had austerity as the order 888 00:48:17,920 --> 00:48:20,600 Speaker 1: of the day, they've been tossed out. I look what's 889 00:48:20,600 --> 00:48:23,160 Speaker 1: going on in Greece. Hey, we've had enough. We're not 890 00:48:23,239 --> 00:48:25,440 Speaker 1: going to take this anymore, and we're gonna elect a 891 00:48:25,520 --> 00:48:27,759 Speaker 1: new group of people who are going to try something 892 00:48:27,840 --> 00:48:30,680 Speaker 1: else because austerity doesn't seem to be working too well 893 00:48:30,760 --> 00:48:32,839 Speaker 1: over there. You're right, and so that's what you think about. 894 00:48:32,840 --> 00:48:37,120 Speaker 1: What about social unrest, it's a problem. And now understand 895 00:48:37,280 --> 00:48:40,320 Speaker 1: in France when they threatened to cut vacations from sixteen 896 00:48:40,760 --> 00:48:44,080 Speaker 1: to fifteen weeks, they're rioting in the streets. The US 897 00:48:45,200 --> 00:48:47,640 Speaker 1: we tend to be a little more tolerant of that, 898 00:48:47,920 --> 00:48:51,799 Speaker 1: where where I think philosophically we haven't wrapped our heads 899 00:48:51,840 --> 00:48:55,279 Speaker 1: around as much of the safety net here as they 900 00:48:55,480 --> 00:48:58,080 Speaker 1: they're used to in in Europe. I think there are 901 00:48:58,120 --> 00:49:01,160 Speaker 1: a lot of reasons for that philosophical difference. But at 902 00:49:01,160 --> 00:49:05,800 Speaker 1: a certain point it looked like the US um electorate 903 00:49:05,920 --> 00:49:07,920 Speaker 1: was going to get angry, and then it just kind 904 00:49:07,920 --> 00:49:11,040 Speaker 1: of faded away. It dissipated. We have a much shorter 905 00:49:11,120 --> 00:49:14,359 Speaker 1: attention span, apparently on this side of the Atlantic than 906 00:49:14,760 --> 00:49:17,879 Speaker 1: than they do. I also think the economy just came back. 907 00:49:17,960 --> 00:49:20,440 Speaker 1: It came back. I mean, think about the unemployment rate 908 00:49:20,880 --> 00:49:25,600 Speaker 1: fell sharply. Um it cures a lot. If you have 909 00:49:25,640 --> 00:49:29,480 Speaker 1: stronger economic growth, people have jobs, feel a lot better 910 00:49:29,480 --> 00:49:32,719 Speaker 1: about what's happening in policy. They're not marching on d 911 00:49:32,880 --> 00:49:36,120 Speaker 1: C when when the unemployment rate drops in half. Yeah, 912 00:49:36,239 --> 00:49:38,560 Speaker 1: not to the same extent, that's for sure. So so 913 00:49:38,719 --> 00:49:41,680 Speaker 1: now let me ask you, UM, let's let's shift away 914 00:49:41,840 --> 00:49:45,880 Speaker 1: from from the crisis, and let's shift away from um 915 00:49:46,120 --> 00:49:51,160 Speaker 1: the austerity argument. Um, what's the big problem with forecasting 916 00:49:51,360 --> 00:49:55,560 Speaker 1: and economists. It's one of the biggest criticisms we see 917 00:49:55,719 --> 00:49:58,560 Speaker 1: is g economists makes these forecasts and they're always wrong. 918 00:49:59,160 --> 00:50:03,120 Speaker 1: What the wrong? Well, someone somebody randomly is going to 919 00:50:03,200 --> 00:50:07,800 Speaker 1: be right. But why the obsession with predictions from you know, 920 00:50:07,880 --> 00:50:11,000 Speaker 1: it's funny you say when you described your job, almost 921 00:50:11,160 --> 00:50:14,560 Speaker 1: nothing you said is And now I'm gonna tell clients 922 00:50:14,600 --> 00:50:16,960 Speaker 1: here's where I think payroll is going to be in 923 00:50:17,080 --> 00:50:18,560 Speaker 1: a month, and here's where the dad was going to be. 924 00:50:18,600 --> 00:50:21,160 Speaker 1: And I do that. I don't forecast the market, but 925 00:50:21,280 --> 00:50:25,320 Speaker 1: I do forecasts the economy, and I always, I always 926 00:50:25,480 --> 00:50:28,600 Speaker 1: try to represent both sides of the argument by saying, 927 00:50:28,760 --> 00:50:31,160 Speaker 1: you know, here's my baseline view, but here's what can 928 00:50:31,200 --> 00:50:33,080 Speaker 1: go right, and here's what can go wrong relative to 929 00:50:33,160 --> 00:50:35,320 Speaker 1: that view. But when you ask that question, I always 930 00:50:35,360 --> 00:50:37,600 Speaker 1: think back to this conversation I had with my grandfather 931 00:50:38,760 --> 00:50:42,280 Speaker 1: who I who I adored um when I first started 932 00:50:42,320 --> 00:50:45,160 Speaker 1: in the industry, and he said, break guy. He said, 933 00:50:45,480 --> 00:50:48,680 Speaker 1: I don't understand. You all look at the same data. 934 00:50:49,120 --> 00:50:51,600 Speaker 1: You all have the same information. Why are there so 935 00:50:51,719 --> 00:50:55,759 Speaker 1: many different forecasts out there? And I was like, you're right, 936 00:50:56,200 --> 00:50:59,560 Speaker 1: But it's the way you interpret the data, and there's 937 00:50:59,600 --> 00:51:01,680 Speaker 1: a lot of judgment that goes into it, and people 938 00:51:01,760 --> 00:51:05,719 Speaker 1: have their own leanings in their own biases. So forecasting is, 939 00:51:06,480 --> 00:51:10,799 Speaker 1: um it's a science, but you know, it's also an 940 00:51:10,920 --> 00:51:15,240 Speaker 1: art to say. To say the least, I'm I'm guilty 941 00:51:15,320 --> 00:51:18,560 Speaker 1: of criticizing economists for playing that game. I wish more 942 00:51:18,640 --> 00:51:21,960 Speaker 1: of them would say, look, I'd rather analyze and explain 943 00:51:22,040 --> 00:51:25,919 Speaker 1: what's going on than project A number of history tells 944 00:51:26,000 --> 00:51:28,880 Speaker 1: us we're not really good at that. As a group, 945 00:51:29,080 --> 00:51:33,160 Speaker 1: we're not especially good at that. Fair fair criticism or not. 946 00:51:33,360 --> 00:51:37,080 Speaker 1: Um No, I mean I think it's fair in the 947 00:51:37,200 --> 00:51:40,920 Speaker 1: sense that there is this tendency to use what happened 948 00:51:40,920 --> 00:51:44,200 Speaker 1: in the past to explain the future. So it's very 949 00:51:44,280 --> 00:51:48,399 Speaker 1: hard to understand turning points. It's always darkest before the dawn, right, 950 00:51:48,480 --> 00:51:50,160 Speaker 1: So it's it's very hard to say that you're ever 951 00:51:50,200 --> 00:51:51,880 Speaker 1: gonna be able to get out of whatever the cycle. 952 00:51:52,000 --> 00:51:53,759 Speaker 1: So when we're in a recession, we're never going to 953 00:51:53,800 --> 00:51:58,400 Speaker 1: gather recession. Yeah. And when we're an expansion, you always 954 00:51:58,400 --> 00:52:00,399 Speaker 1: come up with a reason why the good times will 955 00:52:00,440 --> 00:52:05,080 Speaker 1: just continue. And for those that have bold calls, um, 956 00:52:05,320 --> 00:52:07,759 Speaker 1: you said Nori Overbeini, for example, of making a bold 957 00:52:07,800 --> 00:52:10,960 Speaker 1: call that you know during the the good times that 958 00:52:11,040 --> 00:52:12,760 Speaker 1: they're going to end, and they're going to end badly. 959 00:52:13,920 --> 00:52:15,839 Speaker 1: At some point, you're going to be right with that call, 960 00:52:15,920 --> 00:52:19,160 Speaker 1: and he was, but trying to time, yeah, and that's 961 00:52:19,200 --> 00:52:21,840 Speaker 1: hard and it's hard to do um. And there's always 962 00:52:21,880 --> 00:52:24,680 Speaker 1: this tendency also to return to some sort of steady state, 963 00:52:25,160 --> 00:52:28,120 Speaker 1: some sort of equilibrium, because you don't know what kind 964 00:52:28,160 --> 00:52:31,480 Speaker 1: of shocks are going to hit the economy. So I 965 00:52:31,520 --> 00:52:33,279 Speaker 1: don't want to keep going back to Krugman, but he 966 00:52:33,360 --> 00:52:38,160 Speaker 1: did a whole analysis on fresh water versus salt water economists, 967 00:52:38,719 --> 00:52:42,759 Speaker 1: and there was a lot of self flagellation about the 968 00:52:42,920 --> 00:52:48,040 Speaker 1: profession having not seen the crisis coming beforehand. It well, 969 00:52:48,120 --> 00:52:50,719 Speaker 1: and even in the early stages of it. Kind of 970 00:52:51,160 --> 00:52:54,440 Speaker 1: underestimating geesus is bad and it's going to get a 971 00:52:54,480 --> 00:52:56,880 Speaker 1: whole lot worse. Where where do you come out on 972 00:52:57,000 --> 00:53:01,120 Speaker 1: that sort of you know, deep self analysis of profession 973 00:53:01,160 --> 00:53:05,200 Speaker 1: of economics. Yeah, I mean, listen, it's it's again. It's 974 00:53:05,239 --> 00:53:07,239 Speaker 1: not perfect. I think we you know, you do what 975 00:53:07,360 --> 00:53:09,600 Speaker 1: you can with the data you have and with your judgment. 976 00:53:09,800 --> 00:53:12,080 Speaker 1: But you're right, a lot of people missed it. They 977 00:53:12,160 --> 00:53:15,839 Speaker 1: missed the crisis. Um. I remember even sitting at at 978 00:53:16,280 --> 00:53:18,560 Speaker 1: Lehman Brothers. We had we were working on this piece 979 00:53:18,600 --> 00:53:20,759 Speaker 1: on the housing market, and I was working with our 980 00:53:20,760 --> 00:53:27,040 Speaker 1: mortgage strategy team looking at um the vintages of mortgages, 981 00:53:27,200 --> 00:53:32,240 Speaker 1: so taking um the you know, assuming different default paths, 982 00:53:32,520 --> 00:53:37,200 Speaker 1: paths for mortgages that have been originated given their credit history, 983 00:53:37,360 --> 00:53:39,640 Speaker 1: so assuming their credit history was the likelihood of default. 984 00:53:39,960 --> 00:53:42,120 Speaker 1: And at the time we came up with exceptionally large 985 00:53:42,200 --> 00:53:44,960 Speaker 1: numbers for foreclosure. But we had a conversation saying, oh, well, 986 00:53:45,040 --> 00:53:47,400 Speaker 1: here are the reasons it's not going to happen, because 987 00:53:47,760 --> 00:53:50,080 Speaker 1: that was the view that yeah, you can kind of 988 00:53:50,320 --> 00:53:54,480 Speaker 1: smell that there were issues, and um, you can have 989 00:53:54,640 --> 00:53:58,560 Speaker 1: some problems, but it wouldn't be outright disaster. A lot 990 00:53:58,600 --> 00:54:00,640 Speaker 1: of people like to say they were there was froth 991 00:54:00,760 --> 00:54:04,120 Speaker 1: in the housing market, not a bubble. So you look 992 00:54:04,200 --> 00:54:06,880 Speaker 1: back and you think, oh my gosh, how did I 993 00:54:06,920 --> 00:54:09,319 Speaker 1: ever think that? Look at home prices, reultsi's income, look 994 00:54:09,400 --> 00:54:12,600 Speaker 1: at um, you know all the signs, but cost of 995 00:54:12,680 --> 00:54:16,800 Speaker 1: rental versus close to like several in real time. I 996 00:54:16,920 --> 00:54:21,440 Speaker 1: think it's hard to put that that exceptional scenario. It's 997 00:54:21,440 --> 00:54:23,840 Speaker 1: hard to pencil in that exceptional scenario. And it's always 998 00:54:23,880 --> 00:54:31,400 Speaker 1: hard to imagine the extraordinary circumstances versus the ordinary. UM. 999 00:54:31,600 --> 00:54:34,480 Speaker 1: Oh that's funny. So when you when you're looking at UM, 1000 00:54:34,680 --> 00:54:37,960 Speaker 1: when you're looking at different when you're looking at different 1001 00:54:37,960 --> 00:54:41,600 Speaker 1: scenarios and trying to figure out exactly what's going to 1002 00:54:41,719 --> 00:54:45,080 Speaker 1: blow up and what's not going to blow up, it's 1003 00:54:45,200 --> 00:54:47,360 Speaker 1: much easier to say, well, this is a little crazy 1004 00:54:47,440 --> 00:54:50,000 Speaker 1: and they'll settle down. Then to say, hey, the world's 1005 00:54:50,000 --> 00:54:51,320 Speaker 1: gonna come to an end. This is going to be 1006 00:54:51,400 --> 00:54:53,839 Speaker 1: an abyss. Yeah, of course, of course, it's a much 1007 00:54:53,880 --> 00:54:57,200 Speaker 1: easier view to communicate UM. And I think we've learned 1008 00:54:57,239 --> 00:55:01,600 Speaker 1: from the crisis though, because you look back at what occurred, 1009 00:55:01,840 --> 00:55:04,480 Speaker 1: and I think that we have to realize that, you know, 1010 00:55:04,880 --> 00:55:06,799 Speaker 1: disaster can strike again at some point. So I think 1011 00:55:06,840 --> 00:55:11,000 Speaker 1: there are lessons learned for the average person. For forecasters, 1012 00:55:11,800 --> 00:55:17,880 Speaker 1: but um, you know, there's this tendency to forecast some 1013 00:55:18,080 --> 00:55:20,719 Speaker 1: sort of return to equilibrium which may or may not 1014 00:55:20,800 --> 00:55:23,800 Speaker 1: take place soon or rather than later. So what changes 1015 00:55:23,800 --> 00:55:26,360 Speaker 1: would you like to see take place in the profession 1016 00:55:26,400 --> 00:55:31,080 Speaker 1: of economics as practiced on Wall Street. I think it'd 1017 00:55:31,080 --> 00:55:34,520 Speaker 1: be very helpful to have at all times some sort 1018 00:55:34,600 --> 00:55:40,600 Speaker 1: of modal distribution. So you have to find that best. 1019 00:55:40,800 --> 00:55:43,440 Speaker 1: So you give a forecast, You have to give a forecast. 1020 00:55:43,520 --> 00:55:46,120 Speaker 1: Here's where I see GDP growth, Here's where I see jobs, 1021 00:55:46,239 --> 00:55:48,640 Speaker 1: Here's where I see the fed um. But what's my 1022 00:55:48,719 --> 00:55:52,360 Speaker 1: distribution of risks? Where's the risks around that forecast? Are 1023 00:55:52,400 --> 00:55:54,960 Speaker 1: they leaning to the down side to the upside um? 1024 00:55:55,640 --> 00:55:57,239 Speaker 1: I think that would go a long way in terms 1025 00:55:57,280 --> 00:56:00,120 Speaker 1: of communicating the views and helping market participants. And and 1026 00:56:00,200 --> 00:56:02,000 Speaker 1: I do that. I think we all do it to 1027 00:56:02,040 --> 00:56:05,360 Speaker 1: a certain extent, but maybe to formalize it would be helpful. 1028 00:56:05,680 --> 00:56:08,080 Speaker 1: So in other words, it's not just the number, but 1029 00:56:08,200 --> 00:56:12,200 Speaker 1: the context and the potential upside and downside to the Yeah, 1030 00:56:12,239 --> 00:56:15,160 Speaker 1: so rather than saying our view is for three percent growth, 1031 00:56:15,280 --> 00:56:17,480 Speaker 1: you say our view is the economy will realize three 1032 00:56:17,520 --> 00:56:21,120 Speaker 1: percent growth, but the risks are that there's a higher 1033 00:56:21,360 --> 00:56:23,839 Speaker 1: probability of a two percent than four percent. So now 1034 00:56:23,960 --> 00:56:26,719 Speaker 1: let's you know, we skipped over the capex question. Let's 1035 00:56:26,800 --> 00:56:32,200 Speaker 1: let's let's address that. Um. We've seen the uptick endurable 1036 00:56:32,239 --> 00:56:35,400 Speaker 1: goods at least and how in h automobiles, but not 1037 00:56:35,600 --> 00:56:39,640 Speaker 1: in other goods. And we've seen kind of soft retail 1038 00:56:39,680 --> 00:56:44,720 Speaker 1: spending elsewhere. But the big question is we're not seeing 1039 00:56:44,800 --> 00:56:48,759 Speaker 1: the sort of capex spending on the corporate side that 1040 00:56:48,840 --> 00:56:52,719 Speaker 1: you would expect this far into a recovery. Why not? 1041 00:56:53,160 --> 00:56:56,480 Speaker 1: And when are we gonna see some real corporate capital 1042 00:56:56,560 --> 00:57:02,680 Speaker 1: expenditures that perhaps might be good for both UM, the 1043 00:57:02,760 --> 00:57:08,120 Speaker 1: economy and corporations long term returns. Yeah. So, I think 1044 00:57:08,440 --> 00:57:10,520 Speaker 1: part of the challenge has been that there's a lot 1045 00:57:10,600 --> 00:57:14,440 Speaker 1: of uncertainty about this business cycle. This has been the 1046 00:57:14,520 --> 00:57:19,160 Speaker 1: recovery effits since starts. So that has made many corporations 1047 00:57:19,240 --> 00:57:23,520 Speaker 1: hesitant in terms of doing these bigger, bigger ticket item investments. UM. 1048 00:57:23,760 --> 00:57:26,640 Speaker 1: But the large, large corporations Bardley speaking, should be prepared 1049 00:57:26,680 --> 00:57:28,120 Speaker 1: to do so. If you look at the health of 1050 00:57:28,160 --> 00:57:31,200 Speaker 1: their balance sheets, look at their ability to refinance dead 1051 00:57:31,200 --> 00:57:34,720 Speaker 1: at low levels, UM, they're very sound and and and 1052 00:57:35,120 --> 00:57:37,080 Speaker 1: and should be ready to go in terms of investments. 1053 00:57:37,160 --> 00:57:39,080 Speaker 1: So I hope that it's just a matter of time. 1054 00:57:39,720 --> 00:57:42,240 Speaker 1: Smaller companies have struggled a bit more in the past 1055 00:57:42,240 --> 00:57:45,200 Speaker 1: several years. I haven't had the same access to credit. Um. 1056 00:57:47,240 --> 00:57:50,080 Speaker 1: It's a big it's a big driver, and not only 1057 00:57:50,120 --> 00:57:53,520 Speaker 1: small businesses, but maybe even more importantly, it's new business formation. 1058 00:57:53,680 --> 00:57:58,720 Speaker 1: New business formation is absolutely critical to getting investment to 1059 00:57:58,840 --> 00:58:01,760 Speaker 1: pick up and to get hiring to pick up. And 1060 00:58:01,840 --> 00:58:03,920 Speaker 1: it's been a challenge for new businesses to form in 1061 00:58:04,000 --> 00:58:07,200 Speaker 1: this environment. It's been slower than average. Yes, why do 1062 00:58:07,280 --> 00:58:10,640 Speaker 1: you think that is? Well, I think you know one 1063 00:58:10,720 --> 00:58:12,960 Speaker 1: of the issues, and yes, I focus on housing, so 1064 00:58:13,000 --> 00:58:14,760 Speaker 1: maybe I'm always inclined to go back to it. But 1065 00:58:14,920 --> 00:58:16,760 Speaker 1: I do think part of it links into housing and 1066 00:58:17,040 --> 00:58:20,600 Speaker 1: to the equity issue. A lot of times small new 1067 00:58:20,680 --> 00:58:24,560 Speaker 1: businesses are formed by with drawing money out of your home. 1068 00:58:24,640 --> 00:58:28,880 Speaker 1: It's a it's a personal loan. Yeah, so you you 1069 00:58:29,040 --> 00:58:31,920 Speaker 1: you finance it, you yourself, and you put a lot 1070 00:58:32,000 --> 00:58:35,120 Speaker 1: of your own capital um out front to form a 1071 00:58:35,160 --> 00:58:39,000 Speaker 1: new business. And with difficulty getting home home equity lines 1072 00:58:39,040 --> 00:58:41,520 Speaker 1: of credit, and with a period of negative equity and 1073 00:58:41,600 --> 00:58:44,600 Speaker 1: low equity that's probably made it a bit difficult for 1074 00:58:44,760 --> 00:58:47,160 Speaker 1: some businesses to form. I think maybe one of the 1075 00:58:47,200 --> 00:58:50,200 Speaker 1: other issues is just how a lot of industries has changed. 1076 00:58:50,240 --> 00:58:53,120 Speaker 1: So think about retail. Think about how much the market 1077 00:58:53,200 --> 00:58:56,440 Speaker 1: has changed in just the past ten years. UM we 1078 00:58:56,560 --> 00:58:59,360 Speaker 1: went from an environment where it was very common to 1079 00:58:59,440 --> 00:59:03,080 Speaker 1: go to the walls and two brows and to shop 1080 00:59:03,120 --> 00:59:05,960 Speaker 1: in person, to one where technology has made it so 1081 00:59:06,120 --> 00:59:08,040 Speaker 1: easy to just take out your smartphone or take out 1082 00:59:08,040 --> 00:59:11,320 Speaker 1: your iPhone and click on an app and buy exactly 1083 00:59:11,400 --> 00:59:16,320 Speaker 1: what you need for overnight chipping free, which is amazing. 1084 00:59:16,520 --> 00:59:21,280 Speaker 1: It's amazing. I buy an exurbant amount of stuff on 1085 00:59:21,320 --> 00:59:24,880 Speaker 1: Amazon Prime, especially having a baby at home. You need 1086 00:59:24,920 --> 00:59:26,280 Speaker 1: a lot of things, and you need it quickly, and 1087 00:59:26,320 --> 00:59:27,600 Speaker 1: I don't have to go the store to get it. 1088 00:59:28,280 --> 00:59:32,720 Speaker 1: It's I have. I first became an Amazon client when 1089 00:59:32,880 --> 00:59:36,640 Speaker 1: my college roommate gave me a birthday gift certificate. I 1090 00:59:36,680 --> 00:59:43,000 Speaker 1: want to say, or something like that, and I've kicking 1091 00:59:43,040 --> 00:59:48,320 Speaker 1: and screaming. Finally gave Amazon Prime a try. Because the 1092 00:59:48,480 --> 00:59:51,640 Speaker 1: issue is always what's the big deal. I'll throw something 1093 00:59:51,680 --> 00:59:55,520 Speaker 1: in my um cart and all right, I'll get something else. 1094 00:59:55,560 --> 00:59:57,640 Speaker 1: And you used to be twenty five dollars now it's 1095 00:59:57,680 --> 01:00:02,440 Speaker 1: thirty five some. And what I found with Amazon Prime, 1096 01:00:02,880 --> 01:00:06,200 Speaker 1: which is kind of funny, I'll do the thirty day 1097 01:00:06,520 --> 01:00:10,720 Speaker 1: why not? And I find that you're shopping style just 1098 01:00:10,920 --> 01:00:13,840 Speaker 1: it's like click, one click, you don't even think about 1099 01:00:13,920 --> 01:00:17,880 Speaker 1: it anymore, whatever you want, and and their two days shipping. 1100 01:00:18,560 --> 01:00:22,520 Speaker 1: I don't want to say often, but surprisingly is there 1101 01:00:22,600 --> 01:00:25,520 Speaker 1: the next day. Like if I order something early on 1102 01:00:25,640 --> 01:00:28,040 Speaker 1: a Monday morning, it's in the mail, I get it 1103 01:00:28,120 --> 01:00:32,200 Speaker 1: at Tuesday. If you order it Sunday night, it's not 1104 01:00:32,320 --> 01:00:36,320 Speaker 1: showing up until Tuesday Wednesday. But so it's amazing, how 1105 01:00:36,680 --> 01:00:39,440 Speaker 1: it You know? There was a disc I I had 1106 01:00:39,520 --> 01:00:42,480 Speaker 1: lent to somebody and someone said, oh, it was a 1107 01:00:42,640 --> 01:00:46,840 Speaker 1: Mark Knopfler privateering, which is I'm a huge Dire Straits 1108 01:00:46,880 --> 01:00:49,560 Speaker 1: fan and Mark Nof was his fabulous guitarist, and a 1109 01:00:49,640 --> 01:00:52,080 Speaker 1: buddy call to say he's poppy chewed up the disk 1110 01:00:52,160 --> 01:00:54,480 Speaker 1: and he really I had no problem. We were literally 1111 01:00:54,600 --> 01:00:57,240 Speaker 1: on the phone having a conversation and by the time 1112 01:00:57,360 --> 01:01:00,720 Speaker 1: the conversation finished, he says, you know, don't worry, I'll 1113 01:01:00,760 --> 01:01:02,360 Speaker 1: they'll get you another one. I go too late already 1114 01:01:02,440 --> 01:01:07,240 Speaker 1: ordered like we it was like privateering into the thing 1115 01:01:07,480 --> 01:01:13,720 Speaker 1: done like it's it's so easy and instantaneous, it's astonishing. 1116 01:01:13,880 --> 01:01:16,720 Speaker 1: So what does that mean for you? You've mentioned retail? 1117 01:01:16,800 --> 01:01:19,760 Speaker 1: What does this mean for that? We have hundreds of 1118 01:01:19,840 --> 01:01:24,840 Speaker 1: millions of square feet of retail malls and shopping and 1119 01:01:25,680 --> 01:01:28,560 Speaker 1: do we have too big a footprints for retail? Is 1120 01:01:28,600 --> 01:01:31,920 Speaker 1: that something that's gonna really contract based on what's going 1121 01:01:31,960 --> 01:01:34,040 Speaker 1: on with technology? Well, I mean I think we're we're 1122 01:01:34,160 --> 01:01:36,920 Speaker 1: consuming differently as as we just talked about, which means 1123 01:01:36,960 --> 01:01:39,760 Speaker 1: you don't need as much brick and mortar, and maybe 1124 01:01:39,800 --> 01:01:43,440 Speaker 1: you need more warehousing, maybe you need more distribution, distribution 1125 01:01:43,640 --> 01:01:50,280 Speaker 1: and strones exactly. But technologly you can't can't avoid technology 1126 01:01:50,280 --> 01:01:52,600 Speaker 1: and you have to embrace technology and and it creates 1127 01:01:52,600 --> 01:01:55,920 Speaker 1: winners but also creates losers. Are millennials going to the 1128 01:01:56,000 --> 01:01:59,200 Speaker 1: mall the way the baby boom generation would go sports 1129 01:01:59,240 --> 01:02:03,040 Speaker 1: shopping or retail therapy as some people called it? Is this? 1130 01:02:03,680 --> 01:02:06,680 Speaker 1: Is this that different from the early from the previous 1131 01:02:06,960 --> 01:02:09,440 Speaker 1: I mean, I don't know, it seems to be. I 1132 01:02:09,480 --> 01:02:12,680 Speaker 1: think the other issue is that there's been people staying 1133 01:02:12,760 --> 01:02:16,960 Speaker 1: close to city centers, uh for for longer. Um, So 1134 01:02:17,120 --> 01:02:19,800 Speaker 1: if you're living in an urban area then you don't 1135 01:02:19,840 --> 01:02:24,120 Speaker 1: have as much access to the mall, and um, what 1136 01:02:24,200 --> 01:02:26,160 Speaker 1: do you have access to everything else? You have access 1137 01:02:26,240 --> 01:02:30,280 Speaker 1: to everything else, which is at seven Um. But yeah, 1138 01:02:30,520 --> 01:02:32,960 Speaker 1: I think you do shop a bit differently. For I 1139 01:02:33,000 --> 01:02:34,560 Speaker 1: mean for me, I live in the city. We have 1140 01:02:34,960 --> 01:02:38,800 Speaker 1: you know, a doorman, you you can you can blow 1141 01:02:38,800 --> 01:02:42,040 Speaker 1: out everyone online. It ships there, sit you don't. Yeah, 1142 01:02:42,080 --> 01:02:45,040 Speaker 1: it's just the convenience is exceptional. So um. When I 1143 01:02:45,120 --> 01:02:48,040 Speaker 1: lived in Manhattan, we would have people visit me, visit 1144 01:02:48,120 --> 01:02:50,400 Speaker 1: us in the apartment. My favorite thing was to show 1145 01:02:50,480 --> 01:02:54,000 Speaker 1: them two stacks of menus. This giant stack are the 1146 01:02:54,080 --> 01:02:57,680 Speaker 1: restaurants that will deliver to us. This smaller stack, these 1147 01:02:57,720 --> 01:02:59,840 Speaker 1: are the restaurants that will deliver twenty four hours a day. 1148 01:03:00,440 --> 01:03:03,080 Speaker 1: It was. It was crazy. And when you move out 1149 01:03:03,120 --> 01:03:06,320 Speaker 1: of the city, that's the first thing you miss is Wait, 1150 01:03:06,400 --> 01:03:08,560 Speaker 1: I could get parogi dropped off at my door at 1151 01:03:08,600 --> 01:03:10,600 Speaker 1: two in the morning. That's amazing. It will be a 1152 01:03:10,640 --> 01:03:13,280 Speaker 1: shock to our system at some point. We're trying to 1153 01:03:13,320 --> 01:03:15,280 Speaker 1: hold out. The trade off is you just end up 1154 01:03:15,280 --> 01:03:19,120 Speaker 1: with immense amounts of closet space, like to a My 1155 01:03:19,280 --> 01:03:23,000 Speaker 1: first apartment was a four squift with studio on seventeen 1156 01:03:23,080 --> 01:03:26,040 Speaker 1: and third that literally if you the joke was if 1157 01:03:26,080 --> 01:03:27,520 Speaker 1: you wanted to change your mind, you had to step 1158 01:03:27,560 --> 01:03:30,800 Speaker 1: out into the all way, so you know, enough room. Um, 1159 01:03:31,920 --> 01:03:34,800 Speaker 1: but then now you you end up in the bourbs, 1160 01:03:34,840 --> 01:03:37,840 Speaker 1: and it's just it's a whole different. It's a series 1161 01:03:37,880 --> 01:03:40,479 Speaker 1: of trade offs that I loved being able to life. 1162 01:03:41,480 --> 01:03:43,280 Speaker 1: I guess it really, I guess it really is. So 1163 01:03:43,440 --> 01:03:46,280 Speaker 1: let me ask you about another trade off, um, which 1164 01:03:46,320 --> 01:03:49,720 Speaker 1: a mutual friend asked me to ask you, Um, what 1165 01:03:51,000 --> 01:03:54,800 Speaker 1: research of yours are you especially proud of and and 1166 01:03:55,200 --> 01:03:58,640 Speaker 1: whether or not you nailed the call or a particularly 1167 01:03:58,800 --> 01:04:02,520 Speaker 1: contrary call you had made. What what sort of piece 1168 01:04:02,560 --> 01:04:05,320 Speaker 1: of research? Really? Can you look back and say that 1169 01:04:05,440 --> 01:04:08,320 Speaker 1: was a really great piece of thinking called the bottom 1170 01:04:08,360 --> 01:04:12,040 Speaker 1: and home prices which we were right on, which was great. Um, 1171 01:04:12,800 --> 01:04:15,959 Speaker 1: So March two thousand and twelve put out a piece 1172 01:04:16,000 --> 01:04:20,160 Speaker 1: sing home prices are bottoming now, and they did and 1173 01:04:20,200 --> 01:04:23,720 Speaker 1: the recovery started. So we nailed that call. Um, you 1174 01:04:23,760 --> 01:04:25,880 Speaker 1: get a lot of pushback from that, got a lot 1175 01:04:25,960 --> 01:04:28,840 Speaker 1: of pushback from it. Um, Yeah, home prices are not 1176 01:04:28,920 --> 01:04:30,920 Speaker 1: going to rise. I haven't fallen enough. Why would they 1177 01:04:30,960 --> 01:04:34,680 Speaker 1: be stabilizing in this environment. Um, what's your answer to that? 1178 01:04:34,760 --> 01:04:37,400 Speaker 1: What did you say to people that you had, Um, 1179 01:04:37,840 --> 01:04:41,240 Speaker 1: you had a buyer that Um, you had a seller 1180 01:04:41,320 --> 01:04:45,080 Speaker 1: who was highly motivated and you had a buyer who 1181 01:04:45,160 --> 01:04:47,480 Speaker 1: was also very Obviously they were able to find that 1182 01:04:47,640 --> 01:04:50,680 Speaker 1: market clearing price. Um, which meant a lot of pain. 1183 01:04:50,840 --> 01:04:53,680 Speaker 1: But that's been found, and we're now at a situation 1184 01:04:53,720 --> 01:04:57,240 Speaker 1: where inventory is low. We were looking at twelve months 1185 01:04:57,320 --> 01:04:59,960 Speaker 1: to what five months of and it went pretty fat. 1186 01:05:00,240 --> 01:05:02,920 Speaker 1: So it seemed like we were kind of primed for, um, 1187 01:05:03,240 --> 01:05:05,800 Speaker 1: some stabilization and home prices. Now, did we call for 1188 01:05:05,880 --> 01:05:08,959 Speaker 1: ten percent appreciation two thousand thirteen, No, we were looking 1189 01:05:09,040 --> 01:05:11,120 Speaker 1: for something a bit lower, but for two thousand twelve, 1190 01:05:11,240 --> 01:05:14,600 Speaker 1: just timing that turn, we were right, and um, we're 1191 01:05:14,600 --> 01:05:15,880 Speaker 1: in front of the game. And I remember I went 1192 01:05:15,960 --> 01:05:18,800 Speaker 1: on Bloomberg Surveillance and on Tom King's show the day 1193 01:05:18,840 --> 01:05:21,360 Speaker 1: we published that note. You know, I look back at 1194 01:05:21,400 --> 01:05:23,280 Speaker 1: that and you know, taught me a big, big deal 1195 01:05:23,320 --> 01:05:26,080 Speaker 1: out of it, rightfully, So you know, home prices bought. 1196 01:05:26,080 --> 01:05:28,160 Speaker 1: I mean, Michelle Meyer calls the Bob and home prices 1197 01:05:28,720 --> 01:05:31,160 Speaker 1: and I remember feeling so uncomfortable about them. I was like, 1198 01:05:31,200 --> 01:05:34,800 Speaker 1: oh my gosh, what if we're wrong, and I tried 1199 01:05:34,840 --> 01:05:38,360 Speaker 1: to pull back a bit um and he, knowing Tom, 1200 01:05:38,480 --> 01:05:40,040 Speaker 1: he won't let you. He won't let you, And he 1201 01:05:40,120 --> 01:05:42,920 Speaker 1: still remembers it, and now he's still references that. So 1202 01:05:43,280 --> 01:05:45,120 Speaker 1: I feel really proud about that. So now let me 1203 01:05:45,200 --> 01:05:47,360 Speaker 1: ask you the contrary of that, what what sort of 1204 01:05:47,400 --> 01:05:49,960 Speaker 1: research piece do you wish you could take back that 1205 01:05:50,080 --> 01:05:53,720 Speaker 1: you never hit the published button on? Uh? I would 1206 01:05:53,760 --> 01:05:57,200 Speaker 1: say it was a piece on labor force participation. Let's 1207 01:05:57,200 --> 01:06:01,720 Speaker 1: say two thousand eleven or so. Now, for those listeners 1208 01:06:01,720 --> 01:06:04,560 Speaker 1: who aren't as wonky as as the rest of them, 1209 01:06:05,240 --> 01:06:09,080 Speaker 1: how many people are actively in the labor force, meaning 1210 01:06:09,720 --> 01:06:14,120 Speaker 1: a person who is of employment age. But besides, I'm 1211 01:06:15,800 --> 01:06:18,560 Speaker 1: not working, I'm not looking for work. I'm just I'm 1212 01:06:18,640 --> 01:06:20,800 Speaker 1: complete withdrawing for the labor be for uce. Either I'm 1213 01:06:20,800 --> 01:06:24,400 Speaker 1: going back to school or I'm dropping um adelaide force 1214 01:06:24,480 --> 01:06:27,240 Speaker 1: to raise a child or something. But I'm not an 1215 01:06:27,280 --> 01:06:30,640 Speaker 1: active participant in the labor force. That peaked in the 1216 01:06:30,920 --> 01:06:34,320 Speaker 1: late nineties, didn't it? Um? It did so right before 1217 01:06:34,320 --> 01:06:37,560 Speaker 1: the two thousand one recession. Participation rate peaked and it's 1218 01:06:37,600 --> 01:06:39,760 Speaker 1: been on. It was not like a gradual downward shift. 1219 01:06:40,040 --> 01:06:42,720 Speaker 1: Had some some cyclicality around the two thousand one recession, 1220 01:06:43,120 --> 01:06:46,520 Speaker 1: but then when this recession hit it it felt like 1221 01:06:46,680 --> 01:06:49,320 Speaker 1: it just collapsed. In my view at the time was 1222 01:06:49,400 --> 01:06:51,560 Speaker 1: it fell too fast and that there's room for cyclico 1223 01:06:51,600 --> 01:06:54,320 Speaker 1: advancement and we'd be able to see a rebound the participation, right, 1224 01:06:54,560 --> 01:06:56,960 Speaker 1: I don't think I appreciate enough how much demographics were 1225 01:06:56,960 --> 01:06:59,280 Speaker 1: playing a role. UM. So we wrote a piece, you know, 1226 01:06:59,360 --> 01:07:01,080 Speaker 1: let the lay before to be with you, arguing that 1227 01:07:01,120 --> 01:07:02,920 Speaker 1: the participation ary was going to pick up and that 1228 01:07:03,040 --> 01:07:05,960 Speaker 1: would that's a clever title, yeah you have. That's one 1229 01:07:06,000 --> 01:07:09,080 Speaker 1: thing that Wall Street economists you have to have good titles. UM. 1230 01:07:10,400 --> 01:07:13,080 Speaker 1: And arguing the participation rate would would pick up. It 1231 01:07:13,160 --> 01:07:16,040 Speaker 1: creates some stickiness the unemployment rate and it was not 1232 01:07:16,240 --> 01:07:18,920 Speaker 1: the right call. And in fact, the part that was 1233 01:07:18,960 --> 01:07:22,000 Speaker 1: around two that's eleven now. Hasn't it begun to stabilize. 1234 01:07:22,040 --> 01:07:24,840 Speaker 1: It didn't really stabilize until last year, so they was 1235 01:07:24,880 --> 01:07:27,440 Speaker 1: further downside and the unemployment rate fell faster than what 1236 01:07:27,560 --> 01:07:32,480 Speaker 1: we were predicting. UM. And the odd odd notation of 1237 01:07:32,600 --> 01:07:35,680 Speaker 1: the labor force participation rate is as you have more 1238 01:07:35,720 --> 01:07:38,360 Speaker 1: people coming back into the labor for us looking for work, 1239 01:07:38,760 --> 01:07:43,640 Speaker 1: you'll actually end up seeing and improving economy raises unemployment 1240 01:07:43,760 --> 01:07:45,840 Speaker 1: rate described that. I know a lot of people are 1241 01:07:46,000 --> 01:07:51,120 Speaker 1: perplexed by that. So the participation rate matters because it 1242 01:07:51,200 --> 01:07:54,000 Speaker 1: tells you how many people are out there looking. So 1243 01:07:54,160 --> 01:07:57,280 Speaker 1: even if you have um you know, a stronger economy, 1244 01:07:57,360 --> 01:08:00,440 Speaker 1: if that healthier job growth encourages people to come back 1245 01:08:00,480 --> 01:08:02,960 Speaker 1: in the labor force, it makes it appear as though 1246 01:08:02,960 --> 01:08:06,840 Speaker 1: the unemployment rate is actually more elevated than it is. UM. Now, 1247 01:08:06,920 --> 01:08:09,080 Speaker 1: if the participation rey falls, if your people are looking 1248 01:08:09,160 --> 01:08:12,160 Speaker 1: for work, uh, and of those looking for work, some 1249 01:08:12,240 --> 01:08:15,880 Speaker 1: of which are unemployed looking for work, obviously the unemployment 1250 01:08:15,960 --> 01:08:19,240 Speaker 1: rate has downside biased. So it's not just and I 1251 01:08:19,360 --> 01:08:21,280 Speaker 1: think I talked around it a little bit, but the 1252 01:08:22,520 --> 01:08:25,400 Speaker 1: clear answer is that the unemployment rate is not just 1253 01:08:25,520 --> 01:08:28,160 Speaker 1: influenced by the number of unemployed workers. It's influenced by 1254 01:08:28,160 --> 01:08:30,320 Speaker 1: the number of people looking for a job. So you 1255 01:08:30,400 --> 01:08:34,400 Speaker 1: can sometimes perversely have a rising unemployment rate because the 1256 01:08:34,439 --> 01:08:37,280 Speaker 1: economy the job market is actually getting It's more it's 1257 01:08:37,320 --> 01:08:39,759 Speaker 1: it's hard to see it actually rise when the economy 1258 01:08:39,880 --> 01:08:43,280 Speaker 1: is improving, but it's more that it's sticky. HM. So 1259 01:08:43,680 --> 01:08:46,000 Speaker 1: last last question, because I know you have to get 1260 01:08:46,040 --> 01:08:48,040 Speaker 1: out of here and it's already late in the day. 1261 01:08:48,880 --> 01:08:51,360 Speaker 1: This so much fun. What is what is your So 1262 01:08:51,520 --> 01:08:53,800 Speaker 1: let's talk about what is your what's your favorite part 1263 01:08:53,880 --> 01:08:56,920 Speaker 1: of the job, and um, what changes do you see 1264 01:08:57,040 --> 01:09:01,360 Speaker 1: coming for the role of economists on Wall Street. That's 1265 01:09:01,840 --> 01:09:04,840 Speaker 1: that's a tricky one. Um. Favorite part of the job, 1266 01:09:05,160 --> 01:09:09,639 Speaker 1: I think, um, the amount of adrenaline I have while 1267 01:09:10,080 --> 01:09:14,400 Speaker 1: doing the job. So it's it's it's fast paced, it's fun, 1268 01:09:14,680 --> 01:09:18,519 Speaker 1: it's constant. Um, you're in demand. People want to talk 1269 01:09:18,600 --> 01:09:21,640 Speaker 1: to they want to understand what you're thinking. Um. And 1270 01:09:21,840 --> 01:09:25,680 Speaker 1: that's that's that's really that's that that pumps you up. 1271 01:09:25,760 --> 01:09:28,080 Speaker 1: So I'm excited to go to work. I feel, um, 1272 01:09:28,400 --> 01:09:30,439 Speaker 1: I feel alive. I'm in the office. It's it's great, 1273 01:09:30,479 --> 01:09:33,000 Speaker 1: no matter how tired I might be. So being on 1274 01:09:33,040 --> 01:09:35,840 Speaker 1: the training floor, being involved in the markets, and being 1275 01:09:36,400 --> 01:09:42,200 Speaker 1: able to have conversations with exceptionally smart people is is wonderful. Um. 1276 01:09:42,360 --> 01:09:44,720 Speaker 1: So I love that. I love that about the job. Um. 1277 01:09:44,880 --> 01:09:48,240 Speaker 1: I've really enjoyed the media aspect too. I like public speaking. 1278 01:09:48,520 --> 01:09:51,040 Speaker 1: I like I enjoy being on TV. I enjoy being 1279 01:09:51,080 --> 01:09:52,960 Speaker 1: on the radio. I enjoy being able to communicate my 1280 01:09:53,040 --> 01:09:56,160 Speaker 1: views to the public and and hearing the feedback that's 1281 01:09:56,200 --> 01:09:58,560 Speaker 1: really fun. You know, not everybody agrees and I and 1282 01:09:58,760 --> 01:10:00,280 Speaker 1: and I'm okay with that, And I want to hear 1283 01:10:00,280 --> 01:10:02,320 Speaker 1: where there's a difference of views, and I like the debate. 1284 01:10:02,360 --> 01:10:04,000 Speaker 1: I think it's I think it's healthy, and I think 1285 01:10:04,040 --> 01:10:07,760 Speaker 1: it's exciting. Um. Where is the industry going for economists 1286 01:10:07,760 --> 01:10:09,360 Speaker 1: on Wall Street? Well, I think you could argue that 1287 01:10:09,479 --> 01:10:16,360 Speaker 1: in general, the industry has shrunk, and so clearly opportunities 1288 01:10:16,360 --> 01:10:19,519 Speaker 1: for economist on Wall Street sunk as well. UM. I 1289 01:10:19,600 --> 01:10:21,960 Speaker 1: think one of the big questions that it is thinking 1290 01:10:22,080 --> 01:10:24,040 Speaker 1: is how do you know, how do you monetize research? 1291 01:10:24,160 --> 01:10:29,519 Speaker 1: Research is extremely important? Um, but if you're in a 1292 01:10:29,600 --> 01:10:32,720 Speaker 1: cost cutting environment, Um, you know, how do you how 1293 01:10:32,800 --> 01:10:35,000 Speaker 1: do you how do you make it as valuable as 1294 01:10:35,040 --> 01:10:36,840 Speaker 1: you can? So I think we always have to keep 1295 01:10:36,840 --> 01:10:39,040 Speaker 1: that in mind. Keep that in mind is that at 1296 01:10:39,040 --> 01:10:40,840 Speaker 1: the end of the day, if you're a Welshire economists, 1297 01:10:40,920 --> 01:10:42,920 Speaker 1: do you have to produce something that's going to be 1298 01:10:43,040 --> 01:10:48,360 Speaker 1: important and going to be relevant for your clients? Um, 1299 01:10:48,640 --> 01:10:52,040 Speaker 1: both internal and external clients that they're willing to pay something, 1300 01:10:52,200 --> 01:10:54,720 Speaker 1: willing to pay something for Michelle. This has been an 1301 01:10:54,720 --> 01:10:58,760 Speaker 1: absolute delight we've been speaking to Michelle Meyer. She is 1302 01:10:59,560 --> 01:11:05,360 Speaker 1: the chief economist of Worldwide Bank America. Mery Lynch, as 1303 01:11:05,439 --> 01:11:07,720 Speaker 1: the show goes on to get so, what is your 1304 01:11:07,760 --> 01:11:12,120 Speaker 1: exact title? Deputy Deputy head of US Economics. Okay, and 1305 01:11:12,160 --> 01:11:14,920 Speaker 1: you worked directly with Ethan Harris, who's the chief? Who 1306 01:11:15,040 --> 01:11:19,040 Speaker 1: is the chief? He's the co head of Global Economics. 1307 01:11:19,200 --> 01:11:22,840 Speaker 1: The Developed Economics team reports into him. And if somebody, now, 1308 01:11:22,960 --> 01:11:25,200 Speaker 1: most of your stuff is behind a firewall, if someone 1309 01:11:25,720 --> 01:11:28,320 Speaker 1: wanted to find your work, how would they how would 1310 01:11:28,320 --> 01:11:31,720 Speaker 1: they find it? Well? Bank America is a very large organization. 1311 01:11:31,920 --> 01:11:33,679 Speaker 1: So the good news is that a lot of people 1312 01:11:33,720 --> 01:11:35,720 Speaker 1: do bank with us or have some exposure to to 1313 01:11:35,920 --> 01:11:38,559 Speaker 1: Bank America. And if you do, UM, you can't get 1314 01:11:38,560 --> 01:11:40,960 Speaker 1: access to our research on the I get stuff from 1315 01:11:41,000 --> 01:11:46,360 Speaker 1: you guys every day in UM and through Bloomberg and 1316 01:11:46,439 --> 01:11:50,280 Speaker 1: through you know, other types of blogs like yourself you 1317 01:11:50,400 --> 01:11:53,280 Speaker 1: can get you can get information, So it's out there. 1318 01:11:53,920 --> 01:11:57,800 Speaker 1: We've been speaking with Michelle Meyer of Bank America. Merrill Lynch. 1319 01:11:58,400 --> 01:12:02,200 Speaker 1: If you've enjoyed this podcast, UM, look an inch higher 1320 01:12:02,280 --> 01:12:04,840 Speaker 1: or an inch lower on iTunes and you'll see all 1321 01:12:04,920 --> 01:12:08,840 Speaker 1: the rest of our podcasts. We're up to thirty something 1322 01:12:08,880 --> 01:12:12,400 Speaker 1: almost forty podcasts. Be sure and check out my daily 1323 01:12:12,520 --> 01:12:16,160 Speaker 1: column on Bloomberg View dot com or my blog at 1324 01:12:16,200 --> 01:12:19,479 Speaker 1: rid Halts dot com. You can follow me at rid Halts. 1325 01:12:19,840 --> 01:12:22,719 Speaker 1: I'm Barry Ridholts. You've been listening to Masters in Business 1326 01:12:23,080 --> 01:12:27,600 Speaker 1: on Bloomberg Radio. You're listening to Masters in Business with 1327 01:12:27,720 --> 01:12:30,040 Speaker 1: Barry rid Holts on Bloomberg Radio.