1 00:00:02,240 --> 00:00:06,840 Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio. 2 00:00:07,120 --> 00:00:10,320 Speaker 1: This week on the podcast, I have special guests. Her 3 00:00:10,400 --> 00:00:14,720 Speaker 1: name is Claudia Sam and if that name sounds vaguely familiar, 4 00:00:15,000 --> 00:00:18,759 Speaker 1: she is the person who invented the some rule, which 5 00:00:18,840 --> 00:00:22,800 Speaker 1: essentially is a way to identify when you are in 6 00:00:22,880 --> 00:00:27,319 Speaker 1: a recession in real time. Traditionally, we wait for the 7 00:00:27,400 --> 00:00:32,400 Speaker 1: official n B e R proclamation. Usually it's a year 8 00:00:32,479 --> 00:00:37,440 Speaker 1: or so later. They were surprisingly quick to declare recession 9 00:00:37,520 --> 00:00:40,320 Speaker 1: and it was either March or April um. The some 10 00:00:40,600 --> 00:00:44,840 Speaker 1: rule essentially gives you a way, by using unemployment data 11 00:00:45,240 --> 00:00:48,640 Speaker 1: to figure out in real time when you're in a recession, 12 00:00:49,040 --> 00:00:52,720 Speaker 1: and it's really tremendously helpful. I know Claudia from a 13 00:00:52,840 --> 00:00:57,160 Speaker 1: number of economic dinners and events I've attended. I always 14 00:00:57,160 --> 00:01:00,400 Speaker 1: thought she was kind of interesting and wanted to have 15 00:01:00,560 --> 00:01:04,160 Speaker 1: her on the show, and I just need an excuse 16 00:01:04,240 --> 00:01:08,000 Speaker 1: to get her on. And then last month she wrote 17 00:01:08,080 --> 00:01:13,240 Speaker 1: this fiery blog post economics is a Disgrace. I'll link 18 00:01:13,319 --> 00:01:18,720 Speaker 1: to it on the blog, and and she specifically calls 19 00:01:18,720 --> 00:01:22,240 Speaker 1: out people by names, she calls out institutions, She talks 20 00:01:22,280 --> 00:01:26,440 Speaker 1: about sexism, she talks about racism, She talks about misogyny, 21 00:01:26,520 --> 00:01:31,640 Speaker 1: she talks about bullying, She does not hesitate to name names. 22 00:01:31,720 --> 00:01:36,360 Speaker 1: And really it was just a blistering blog post. I 23 00:01:36,400 --> 00:01:41,600 Speaker 1: don't say that very often, UM, for someone within an industry, 24 00:01:41,640 --> 00:01:45,399 Speaker 1: within a respected institution, to say, hey, this is an 25 00:01:45,440 --> 00:01:49,240 Speaker 1: utter mess. We better get our acts together soon. And 26 00:01:50,080 --> 00:01:53,240 Speaker 1: you know, by the way physician heal thyself, it was 27 00:01:53,320 --> 00:01:58,320 Speaker 1: really something that that caught my eye. UM. Economics isn't 28 00:01:58,360 --> 00:02:02,120 Speaker 1: the only industry that has these sorts of issues. Between 29 00:02:02,480 --> 00:02:04,760 Speaker 1: the Me Too movement and what we've been seeing with 30 00:02:04,800 --> 00:02:08,320 Speaker 1: Black Lives Matter, it's pretty clear that that this is 31 00:02:08,480 --> 00:02:13,080 Speaker 1: endemic in a lot of institutions and a lot of professions. 32 00:02:13,080 --> 00:02:15,520 Speaker 1: But it's kind of rare to see somebody who's within 33 00:02:15,680 --> 00:02:19,240 Speaker 1: that institution calling it out. We also talk wank out 34 00:02:19,280 --> 00:02:23,880 Speaker 1: about stimulus checks and and recessions and macroeconomic policy and 35 00:02:23,919 --> 00:02:26,840 Speaker 1: what's being done correctly this time and what should have 36 00:02:26,840 --> 00:02:29,720 Speaker 1: been run right In O eight oh nine, it's it's 37 00:02:29,880 --> 00:02:34,360 Speaker 1: good wonky fun. I save all the grievances for the 38 00:02:34,440 --> 00:02:38,040 Speaker 1: last segment, So if that's not UM floating your boat, 39 00:02:38,080 --> 00:02:40,280 Speaker 1: you don't have to listen to that. But she does 40 00:02:40,280 --> 00:02:43,880 Speaker 1: an excellent job explaining what the profession is getting wrong 41 00:02:43,880 --> 00:02:45,960 Speaker 1: and what it needs to fix. And this includes both 42 00:02:45,960 --> 00:02:50,800 Speaker 1: policy and research and publication as well as hiring practices 43 00:02:50,840 --> 00:02:53,840 Speaker 1: and other things. So I think you'll find this very interesting. 44 00:02:54,240 --> 00:03:01,480 Speaker 1: With no further ado, my conversation with Claudia some vis 45 00:03:01,720 --> 00:03:05,799 Speaker 1: is Masters in Business with Barry Ridholts on Bloomberg Radio. 46 00:03:06,600 --> 00:03:10,400 Speaker 1: My special guest this week is Claudia Sam. She is 47 00:03:10,440 --> 00:03:14,960 Speaker 1: the director of macroeconomic Policy at the Washington Center for 48 00:03:15,040 --> 00:03:19,920 Speaker 1: Equitable Growth. She was previously a senior economist at the 49 00:03:20,000 --> 00:03:26,320 Speaker 1: Council of Economic Advisors for the Obama administration. In from 50 00:03:26,480 --> 00:03:31,160 Speaker 1: two thousand and seven to she was a researcher and 51 00:03:31,360 --> 00:03:34,520 Speaker 1: section chief at the Board of Governors of the Federal Reserve, 52 00:03:34,880 --> 00:03:39,680 Speaker 1: where she specialized in macroeconomics and household of finance. She 53 00:03:40,080 --> 00:03:44,000 Speaker 1: is also the creator of the some Rule, which determines 54 00:03:44,120 --> 00:03:49,240 Speaker 1: if a recession is occurring in real time. Claudia Sam, 55 00:03:49,280 --> 00:03:53,160 Speaker 1: Welcome to Bloomberg. Thank you. I'm so happy to be here. 56 00:03:53,720 --> 00:03:56,000 Speaker 1: Tell us about how you found your way to the 57 00:03:56,120 --> 00:04:00,920 Speaker 1: Council of Economic Advisors for the Obama ministry. Yes, so, 58 00:04:01,040 --> 00:04:03,760 Speaker 1: by the time I went to the Council of Economic 59 00:04:03,840 --> 00:04:08,200 Speaker 1: Advisors which was in the summer off. I had been 60 00:04:08,240 --> 00:04:11,680 Speaker 1: at the Board for several years, so I went as 61 00:04:12,000 --> 00:04:16,520 Speaker 1: the macroeconomic senior economists. I covered at the White House 62 00:04:16,760 --> 00:04:22,279 Speaker 1: all of domestic macro and housing policy. So when I arrived, 63 00:04:22,360 --> 00:04:25,080 Speaker 1: I thought, oh wow, they were like a hundred economists 64 00:04:25,200 --> 00:04:28,200 Speaker 1: or more at the Board that cover these two topics. 65 00:04:28,920 --> 00:04:31,400 Speaker 1: And but by the time I went there, I was 66 00:04:31,520 --> 00:04:34,200 Speaker 1: trained to be able to do that. I started in 67 00:04:34,279 --> 00:04:37,920 Speaker 1: two thousand and seven as an expert on consumer spending. 68 00:04:38,920 --> 00:04:43,560 Speaker 1: Over time I got to manage and oversee the staffs forecast. 69 00:04:44,160 --> 00:04:46,360 Speaker 1: I had been able to do a lot of briefings 70 00:04:46,400 --> 00:04:48,719 Speaker 1: and writing. So by the time I went to c A, 71 00:04:48,839 --> 00:04:51,320 Speaker 1: and that is true of everyone that they sent over there, 72 00:04:52,120 --> 00:04:54,840 Speaker 1: I had the experience to step into that role and 73 00:04:54,880 --> 00:04:57,400 Speaker 1: it for me it was really refreshing because I was like, oh, 74 00:04:57,560 --> 00:04:59,960 Speaker 1: I am a generalist. I said, most of my time 75 00:05:00,120 --> 00:05:03,160 Speaker 1: doing business investment. As I said, no one would have 76 00:05:03,200 --> 00:05:06,520 Speaker 1: asked me what I thought about business investment, and there 77 00:05:06,680 --> 00:05:09,480 Speaker 1: was a really rewarding experience. Jason Furman was chair at 78 00:05:09,480 --> 00:05:12,679 Speaker 1: the time. He is excellent. He worked as so hard 79 00:05:13,080 --> 00:05:16,039 Speaker 1: in a good way. Jay Campbell was a member that 80 00:05:16,120 --> 00:05:20,680 Speaker 1: I worked with UH really closely, and I mean really 81 00:05:20,720 --> 00:05:24,719 Speaker 1: everyone that I worked with, from member to senior economists 82 00:05:24,800 --> 00:05:29,200 Speaker 1: to junior economists too, in terms like they were just fabulous. 83 00:05:29,560 --> 00:05:34,560 Speaker 1: My last day adds the Council of Economic Advisors was Brexit, 84 00:05:35,279 --> 00:05:38,840 Speaker 1: and so uh, I'm really good at picking good times, right. 85 00:05:38,880 --> 00:05:41,640 Speaker 1: My first forecast at the FED was the start of 86 00:05:41,680 --> 00:05:44,719 Speaker 1: the Great Recession. My last day at the e A 87 00:05:45,000 --> 00:05:48,159 Speaker 1: was Brexit. I worked all through the weekend. What was 88 00:05:48,200 --> 00:05:51,120 Speaker 1: funny is when I got back to the board on Monday, no, 89 00:05:51,320 --> 00:05:53,839 Speaker 1: it was crickets, Like nobody was going to come ask 90 00:05:53,880 --> 00:05:55,840 Speaker 1: me what I thought about Brexit. We have a whole 91 00:05:55,880 --> 00:06:00,000 Speaker 1: team of international economists. So it was a really interesting experience. 92 00:06:00,040 --> 00:06:03,560 Speaker 1: Ants I'm glad I did it. It really focused my 93 00:06:03,640 --> 00:06:08,640 Speaker 1: mind on what economic policy could be, frankly should be. 94 00:06:09,640 --> 00:06:13,240 Speaker 1: And I'll end this piece with just a funny story 95 00:06:13,440 --> 00:06:17,640 Speaker 1: and how like the journey to the CEA started back 96 00:06:17,680 --> 00:06:21,120 Speaker 1: in undergraduate So I went to Dennison University, a liberal 97 00:06:21,160 --> 00:06:26,440 Speaker 1: arts college, and in my intermediate macro class, Dick Lucier 98 00:06:26,520 --> 00:06:29,560 Speaker 1: taught the class and part of the class was us 99 00:06:29,920 --> 00:06:33,440 Speaker 1: being like we were economists at the count of Economic Advisors. 100 00:06:33,560 --> 00:06:35,680 Speaker 1: We had to cut things out of the newspaper and 101 00:06:35,720 --> 00:06:39,000 Speaker 1: do analysis, and then he role played being the president 102 00:06:39,120 --> 00:06:42,360 Speaker 1: and we had do presentations. I got to when he 103 00:06:43,480 --> 00:06:46,640 Speaker 1: um when I was at the Council of Economic Advisors, 104 00:06:46,640 --> 00:06:48,719 Speaker 1: he came to visit in d C. And I got 105 00:06:48,760 --> 00:06:50,760 Speaker 1: to take him on a tour of the Oval Office. 106 00:06:51,200 --> 00:06:53,560 Speaker 1: So to me, it was just this really special connection 107 00:06:53,760 --> 00:06:55,760 Speaker 1: from how I fell in love with economics as an 108 00:06:55,800 --> 00:06:58,880 Speaker 1: undergraduate and then when I got to contribute as an 109 00:06:58,880 --> 00:07:04,040 Speaker 1: economist to the policy world. Huh. Quite interesting. You were 110 00:07:04,120 --> 00:07:08,200 Speaker 1: also a section chief the Division of Consumer and Community 111 00:07:08,200 --> 00:07:11,920 Speaker 1: Affairs at the FED. What does that mean exactly? What 112 00:07:12,080 --> 00:07:14,360 Speaker 1: is the role of a section chief? Right? So, in 113 00:07:14,440 --> 00:07:17,360 Speaker 1: my last two years as a fellow Reserve, I was 114 00:07:17,440 --> 00:07:20,640 Speaker 1: a section in chief for a research section and the 115 00:07:20,680 --> 00:07:23,240 Speaker 1: Division of Consumer and Community Affair. There were a lot 116 00:07:23,280 --> 00:07:25,440 Speaker 1: of things unique about that because I had moved at 117 00:07:25,480 --> 00:07:29,120 Speaker 1: that point out of a quote unquote economics division. So 118 00:07:29,280 --> 00:07:33,920 Speaker 1: the team that I managed were the only economists doing 119 00:07:34,080 --> 00:07:37,760 Speaker 1: economic research in that whole division. So to me, it 120 00:07:37,840 --> 00:07:40,440 Speaker 1: was very eye opening. I worked with attorneys, I worked 121 00:07:40,440 --> 00:07:45,280 Speaker 1: with policy analysts, and they were all really impressive. The 122 00:07:45,360 --> 00:07:49,480 Speaker 1: division focuses on low and moderate incomes families and communities. 123 00:07:49,880 --> 00:07:52,840 Speaker 1: So they were from the very beginning ahead of the 124 00:07:52,880 --> 00:07:55,920 Speaker 1: game in terms of thinking about diversity and inclusion and 125 00:07:56,920 --> 00:08:02,720 Speaker 1: racial injustice and educational disparity in rural versus urban. So 126 00:08:03,440 --> 00:08:05,800 Speaker 1: that that was a really good experience for me. Back 127 00:08:05,800 --> 00:08:08,360 Speaker 1: to what it means to be a section chief. So 128 00:08:08,520 --> 00:08:11,440 Speaker 1: it is widely known that the section chief is the 129 00:08:11,520 --> 00:08:14,480 Speaker 1: worst job or the hardest job, and the only one 130 00:08:14,520 --> 00:08:17,160 Speaker 1: that comes closed is being a division director. So right, 131 00:08:17,200 --> 00:08:19,400 Speaker 1: that's the very top of the house, and the section 132 00:08:19,440 --> 00:08:23,240 Speaker 1: chief is the first manager job the board. Now it 133 00:08:23,280 --> 00:08:25,320 Speaker 1: didn't when I joined the board, but the board now 134 00:08:25,440 --> 00:08:30,600 Speaker 1: has very intensive management training for section chiefs or anyone 135 00:08:30,640 --> 00:08:32,800 Speaker 1: who starts as a group manager, which is like one 136 00:08:32,880 --> 00:08:38,440 Speaker 1: level down. So anyone who's supervising goes to a manager 137 00:08:38,520 --> 00:08:41,200 Speaker 1: boot camp. It was like three months, every other week, 138 00:08:41,679 --> 00:08:44,520 Speaker 1: three hours, uh, and that was really good. They brought up, 139 00:08:44,640 --> 00:08:48,160 Speaker 1: brought in external consultants. I learned a lot from that. 140 00:08:48,200 --> 00:08:51,200 Speaker 1: I learned a lot from my team, especially the research assistant, 141 00:08:51,480 --> 00:08:55,120 Speaker 1: in how to be a good manager. Now, it won't 142 00:08:55,120 --> 00:08:57,959 Speaker 1: surprise anyone, and this isn't just at the board. You 143 00:08:58,080 --> 00:09:01,480 Speaker 1: get promoted because you're good at doing the job you 144 00:09:01,520 --> 00:09:04,520 Speaker 1: started with, like I was I've made Section chief because 145 00:09:04,559 --> 00:09:07,240 Speaker 1: I'm a very good economist and I could lead my 146 00:09:07,320 --> 00:09:10,960 Speaker 1: team on their economic policy work. That didn't mean I 147 00:09:11,000 --> 00:09:13,959 Speaker 1: knew anything about being a manager, and they don't teach 148 00:09:14,000 --> 00:09:16,280 Speaker 1: us that in the PhD doctoral programs, and often they 149 00:09:16,280 --> 00:09:18,920 Speaker 1: teach us what not to do as a manager. UM 150 00:09:19,000 --> 00:09:21,880 Speaker 1: So that was a really hard year. That was like 151 00:09:22,000 --> 00:09:25,760 Speaker 1: my impostor syndrome year, on par with that year in 152 00:09:25,800 --> 00:09:27,680 Speaker 1: two thousand and eight when I was like, oh my gosh, 153 00:09:27,880 --> 00:09:30,839 Speaker 1: I'm supposed to forecast the US economy in crisis. So 154 00:09:30,880 --> 00:09:32,600 Speaker 1: it was a very different time and I handled it 155 00:09:32,640 --> 00:09:35,960 Speaker 1: weight better than two thousand eight. But it's a tricky job, 156 00:09:36,040 --> 00:09:39,640 Speaker 1: and it's one where the board helps us do a 157 00:09:39,679 --> 00:09:42,440 Speaker 1: good job now. But if you don't do a good job, 158 00:09:42,559 --> 00:09:45,240 Speaker 1: you can not only have a team that's not effective 159 00:09:45,240 --> 00:09:49,360 Speaker 1: at doing policy work, you can really damage people. And 160 00:09:49,440 --> 00:09:51,199 Speaker 1: we don't want to do that because that doesn't help 161 00:09:51,200 --> 00:09:54,800 Speaker 1: any We're going to talk more about that and how 162 00:09:54,880 --> 00:09:59,800 Speaker 1: the UM field, especially the academic programs, not only do 163 00:09:59,880 --> 00:10:03,160 Speaker 1: they not teach management, they really don't teach writing. They 164 00:10:03,160 --> 00:10:06,360 Speaker 1: don't teach a lot of skills that would be helpful. 165 00:10:06,679 --> 00:10:10,240 Speaker 1: So but we'll come back to that. What also makes 166 00:10:10,280 --> 00:10:13,839 Speaker 1: you a little unusual as an economist is you are 167 00:10:13,920 --> 00:10:17,240 Speaker 1: pretty active on Twitter and you maintain an active blog, 168 00:10:17,679 --> 00:10:23,200 Speaker 1: as do I. Why are you uh using these platforms? 169 00:10:23,320 --> 00:10:27,120 Speaker 1: Tell us what an economist gets out of participating in 170 00:10:27,200 --> 00:10:32,920 Speaker 1: social media. So I joined the platforms Twitter. The blogging 171 00:10:33,000 --> 00:10:37,679 Speaker 1: came later. Uh my gateway quote unquote drug to economic 172 00:10:37,760 --> 00:10:42,120 Speaker 1: social media was commenting on economic blogs like marginal Revolution, 173 00:10:42,600 --> 00:10:46,760 Speaker 1: money illusion. Um, that was really how I dipped my 174 00:10:46,840 --> 00:10:51,120 Speaker 1: toe in the water there Twitter. I spent time on it. 175 00:10:51,280 --> 00:10:54,800 Speaker 1: The reason I went to Twitter was because after I'd 176 00:10:54,840 --> 00:10:58,080 Speaker 1: had some difficult periods at the board and also was 177 00:10:58,120 --> 00:11:03,920 Speaker 1: trying to figure out how are all these smart, caring colleagues, Like, 178 00:11:04,000 --> 00:11:06,200 Speaker 1: how are we missing it that the recovery from the 179 00:11:06,200 --> 00:11:09,040 Speaker 1: Great Recession is going to be really slow? I like, 180 00:11:09,080 --> 00:11:13,040 Speaker 1: our staff forecast was consistently too strong, and I and 181 00:11:13,120 --> 00:11:17,400 Speaker 1: there were others were consistently saying, what are you thinking? 182 00:11:17,840 --> 00:11:21,600 Speaker 1: There's no way we have families that are absolutely decimated 183 00:11:21,800 --> 00:11:25,160 Speaker 1: from this recession. And so for me that moment and 184 00:11:25,160 --> 00:11:28,120 Speaker 1: then reflecting back, remember I showed up in the summer 185 00:11:28,160 --> 00:11:31,160 Speaker 1: of two thousand and seven reflecting back, and I was like, 186 00:11:31,200 --> 00:11:34,560 Speaker 1: how did we miss this right, Like, there's all these 187 00:11:34,600 --> 00:11:38,960 Speaker 1: people and that was a moment where I said, Okay, 188 00:11:39,000 --> 00:11:43,600 Speaker 1: maybe it's because we don't have enough diverse voices, we're 189 00:11:43,640 --> 00:11:48,480 Speaker 1: not connected enough to reality. And well Twitter has got 190 00:11:48,520 --> 00:11:51,160 Speaker 1: a lot of diverse voices, right, So I went on 191 00:11:51,240 --> 00:11:55,680 Speaker 1: to econ Twitter. I like to as it would be 192 00:11:55,679 --> 00:11:58,160 Speaker 1: apparent to anyone who knows me, I like to talk 193 00:11:58,160 --> 00:12:00,560 Speaker 1: to people. I like people. I like people that are 194 00:12:00,559 --> 00:12:04,200 Speaker 1: a little prickly. I mean, I'm a macro economist, right like, 195 00:12:04,640 --> 00:12:07,760 Speaker 1: so I went there to hear from people who don't 196 00:12:08,000 --> 00:12:10,720 Speaker 1: they're not inside the building, and frankly, it's probably a 197 00:12:10,720 --> 00:12:12,920 Speaker 1: good idea, Like some of them would be absolutely horrible 198 00:12:13,000 --> 00:12:16,160 Speaker 1: macro forecasters at the board. But that was for me 199 00:12:16,320 --> 00:12:21,640 Speaker 1: very important. Now that was my upside. No one at 200 00:12:21,679 --> 00:12:24,480 Speaker 1: the board saw that as an upside, right, and I 201 00:12:24,600 --> 00:12:29,960 Speaker 1: was a walking downside risk within a very short time 202 00:12:29,960 --> 00:12:32,680 Speaker 1: of being on Twitter. It's very good about it. I 203 00:12:32,679 --> 00:12:35,440 Speaker 1: don't talk about monetary policy, but I was linked to 204 00:12:35,520 --> 00:12:39,000 Speaker 1: things on the board's website like Bernankee gave us speed 205 00:12:39,160 --> 00:12:43,240 Speaker 1: and Da Da Da Da. So I got found out 206 00:12:43,400 --> 00:12:46,960 Speaker 1: by public affairs because I was driving traffic to the 207 00:12:47,000 --> 00:12:51,560 Speaker 1: board's website and yeah, and it was bad. And I 208 00:12:51,600 --> 00:12:54,000 Speaker 1: got called to an off site coffee that was basically like, 209 00:12:54,040 --> 00:12:56,960 Speaker 1: what is wrong with you? You were the only staff 210 00:12:57,000 --> 00:13:02,000 Speaker 1: economist talking about economics on Twitter. And the reward for 211 00:13:02,040 --> 00:13:04,400 Speaker 1: that is I had all of public if not all, 212 00:13:04,440 --> 00:13:08,360 Speaker 1: I had Michelle Smith and several other public affairs people 213 00:13:08,440 --> 00:13:11,600 Speaker 1: following me on Twitter when I would do something that 214 00:13:11,720 --> 00:13:14,679 Speaker 1: they felt was a miss step. Even I've never broke 215 00:13:15,200 --> 00:13:19,640 Speaker 1: like ah, I never talked about um information that wasn't 216 00:13:19,679 --> 00:13:23,280 Speaker 1: public like forecast information. But I would get within a 217 00:13:23,280 --> 00:13:25,760 Speaker 1: half an hour a call from my division director or 218 00:13:25,840 --> 00:13:28,600 Speaker 1: via my boss saying you got you can't do that. 219 00:13:28,640 --> 00:13:30,960 Speaker 1: You gotta do you know. And so there was this 220 00:13:31,080 --> 00:13:35,319 Speaker 1: aspect of surveillance, which I get, Like Michelle Smith, public 221 00:13:35,360 --> 00:13:39,079 Speaker 1: affairs at the Board has such a hard job, and 222 00:13:39,160 --> 00:13:41,280 Speaker 1: every once in a while I stepped in their lane. 223 00:13:41,800 --> 00:13:45,840 Speaker 1: I never meant to like, how how dare you promote 224 00:13:45,920 --> 00:13:49,199 Speaker 1: something that we've hidden in public view on our publicly 225 00:13:49,360 --> 00:13:53,800 Speaker 1: accessible website. Yeah. No. And when my last year at 226 00:13:53,800 --> 00:13:58,280 Speaker 1: the FED, and I really thought, because Howell like loves Twitter, 227 00:13:58,760 --> 00:14:00,880 Speaker 1: right when he was a brand a governor, I was 228 00:14:00,960 --> 00:14:03,840 Speaker 1: in his office with another economist he wanted to understand 229 00:14:03,920 --> 00:14:06,720 Speaker 1: like labor markets superstar effect. We went and talked to 230 00:14:06,800 --> 00:14:08,880 Speaker 1: him at the end of the meeting. He looked at 231 00:14:08,920 --> 00:14:10,600 Speaker 1: me and he's like, oh, yeah, you had a really 232 00:14:10,640 --> 00:14:13,560 Speaker 1: big day. And I'm like, well, duh, I'm here, you know, 233 00:14:13,600 --> 00:14:17,679 Speaker 1: breathing a governor and he's like, no, it's Smiths retweeted 234 00:14:17,760 --> 00:14:22,440 Speaker 1: you on Twitter. I over I know no, because I 235 00:14:22,520 --> 00:14:26,720 Speaker 1: was like, you're on Twitter and you followed Noah and 236 00:14:26,760 --> 00:14:29,720 Speaker 1: you were on Twitter during the day, right. So I 237 00:14:29,840 --> 00:14:32,680 Speaker 1: was just blown. When he became chair, I thought, oh, 238 00:14:32,680 --> 00:14:36,360 Speaker 1: Twitter is gonna be okay. Yeah, that was wrong. Um. 239 00:14:37,800 --> 00:14:40,120 Speaker 1: So I got in trouble two more times because Poal 240 00:14:40,240 --> 00:14:42,160 Speaker 1: read one of my tweets and asked about it and 241 00:14:42,160 --> 00:14:44,680 Speaker 1: he shouldn't be learning anything from my tweets, so I 242 00:14:44,720 --> 00:14:47,240 Speaker 1: was told. And twice I got in trouble for linking 243 00:14:47,240 --> 00:14:50,520 Speaker 1: to the distributional financial accounts on the board's website because 244 00:14:50,520 --> 00:14:52,640 Speaker 1: they didn't want attention drawn to it. And I was 245 00:14:52,640 --> 00:14:54,680 Speaker 1: always like, you know, the board's website is the best 246 00:14:54,680 --> 00:14:58,040 Speaker 1: place to put information you don't want anyone to see. Um, 247 00:14:58,280 --> 00:15:03,560 Speaker 1: but that's hilarious. I love the board. I understand much 248 00:15:03,600 --> 00:15:06,640 Speaker 1: better than I did in the beginning why what I 249 00:15:06,680 --> 00:15:11,640 Speaker 1: was doing could be problematic. And I never never wanted 250 00:15:11,680 --> 00:15:15,560 Speaker 1: to be the person who brought down the bed right 251 00:15:15,800 --> 00:15:20,360 Speaker 1: or cause immense stress. I was just having fun, and 252 00:15:20,440 --> 00:15:22,640 Speaker 1: like I said, I was trying to learn from people 253 00:15:23,160 --> 00:15:25,680 Speaker 1: who weren't like anybody else that was in the building. 254 00:15:26,560 --> 00:15:28,680 Speaker 1: That's so funny that, by the way, bringing down the 255 00:15:28,680 --> 00:15:31,760 Speaker 1: FED is Judy Shelton's job. It's not Clodius Tom's job. 256 00:15:31,880 --> 00:15:34,240 Speaker 1: So we can leave that, we can leave that to home. 257 00:15:34,440 --> 00:15:38,480 Speaker 1: I'm coming now, I know. That's why I'm sticking my 258 00:15:38,520 --> 00:15:42,120 Speaker 1: two bits in. And by the way, my economics gateway 259 00:15:42,200 --> 00:15:47,440 Speaker 1: drug was Brad DeLong, the economist from Berkeley, and he 260 00:15:47,520 --> 00:15:52,160 Speaker 1: was one of the earliest academic bloggers, just musing in 261 00:15:52,280 --> 00:15:56,520 Speaker 1: public on a blog and discussing economic data. And it 262 00:15:56,600 --> 00:16:02,280 Speaker 1: was so refreshing compared to the sort of stayed releases 263 00:16:02,440 --> 00:16:06,000 Speaker 1: from BLS and even back then the Wall Street economists 264 00:16:06,000 --> 00:16:09,880 Speaker 1: were very, very tame, and to have someone come out 265 00:16:09,960 --> 00:16:14,160 Speaker 1: and just like boom, here's what's wrong with the data 266 00:16:14,240 --> 00:16:18,880 Speaker 1: analysis was really a refreshing change of pace. Yeah, and 267 00:16:18,920 --> 00:16:21,240 Speaker 1: I will say there are two things that I really 268 00:16:21,320 --> 00:16:23,880 Speaker 1: like about Brad DeLong on Twitter, Like I liked him 269 00:16:23,920 --> 00:16:26,440 Speaker 1: off Twitter. I've learned a lot from him. One he 270 00:16:26,560 --> 00:16:29,680 Speaker 1: is an economic history why he has a good grounding 271 00:16:29,720 --> 00:16:32,520 Speaker 1: in economic history, that's not the only thing he works. 272 00:16:32,520 --> 00:16:35,560 Speaker 1: And he does a lot in macro space. To his blog, 273 00:16:35,760 --> 00:16:38,280 Speaker 1: I mean he was like live tweeting World War two 274 00:16:38,480 --> 00:16:40,440 Speaker 1: or you know, I mean like it would have it 275 00:16:40,520 --> 00:16:43,760 Speaker 1: showed a side of him that was like not like 276 00:16:44,960 --> 00:16:47,160 Speaker 1: an economy that you wouldn't have seen this in an 277 00:16:47,200 --> 00:16:50,600 Speaker 1: economic seminar. The other thing that Brad does on Twitter, 278 00:16:51,040 --> 00:16:55,520 Speaker 1: which is very rare, is that he engages with people, 279 00:16:56,280 --> 00:17:00,080 Speaker 1: like he will reply to tweets. Have I looked on 280 00:17:00,120 --> 00:17:03,760 Speaker 1: from Paul Krubin's Twitter feed, and I Paul like does 281 00:17:03,840 --> 00:17:07,080 Speaker 1: so much in terms of communicating economics and pushing us 282 00:17:07,119 --> 00:17:11,240 Speaker 1: to think and pushing a broader audience. He never replies 283 00:17:11,520 --> 00:17:15,399 Speaker 1: to tweets, like never, So I like Brad that he 284 00:17:15,480 --> 00:17:19,399 Speaker 1: engages like I like to engage. So that to me 285 00:17:19,600 --> 00:17:22,159 Speaker 1: is like econ Twitter can be a special place, but 286 00:17:22,280 --> 00:17:27,359 Speaker 1: it's hard if it's a lecture and not a conversation. Huh. 287 00:17:27,440 --> 00:17:32,040 Speaker 1: Quite fascinating. So let's talk a little bit about fiscal stimulus. 288 00:17:32,080 --> 00:17:34,760 Speaker 1: You know, when we look back at the financial crisis 289 00:17:34,760 --> 00:17:38,320 Speaker 1: of oh eight oh nine. The vast majority of that 290 00:17:38,400 --> 00:17:41,800 Speaker 1: response seemed to be coming from the Federal Reserve and 291 00:17:41,920 --> 00:17:47,679 Speaker 1: a monetary ast response, not a fiscal stimulus compared to 292 00:17:47,800 --> 00:17:51,080 Speaker 1: this one, How would you do a side by side 293 00:17:51,119 --> 00:17:57,720 Speaker 1: comparison between two thousand and eight and on a fiscal basis. 294 00:17:58,160 --> 00:18:02,560 Speaker 1: So I have done a lot of work thinking about 295 00:18:02,760 --> 00:18:08,040 Speaker 1: how compares to two thousand and eight, And the reason 296 00:18:08,160 --> 00:18:12,880 Speaker 1: for that is I had a very unique experience at 297 00:18:12,880 --> 00:18:16,200 Speaker 1: the Board in terms of understanding what happened in two 298 00:18:16,240 --> 00:18:20,720 Speaker 1: thousand and eight and the years after that. And it 299 00:18:20,800 --> 00:18:25,120 Speaker 1: may is the encounterintuitive. So I covered consumer spending at 300 00:18:25,119 --> 00:18:30,919 Speaker 1: the Federal Reserve. I didn't advise on monetary policy. What 301 00:18:31,080 --> 00:18:33,480 Speaker 1: my job was to do was say, Okay, what's going 302 00:18:33,520 --> 00:18:37,840 Speaker 1: to happen, what is happening for families and they're spending 303 00:18:38,520 --> 00:18:42,159 Speaker 1: in the economy. To do that during the crisis and 304 00:18:42,280 --> 00:18:45,960 Speaker 1: during the recovery, I had to understand and have an opinion, 305 00:18:46,040 --> 00:18:49,879 Speaker 1: expert opinion on what is fiscal relief doing or fiscal 306 00:18:49,920 --> 00:18:52,960 Speaker 1: stimulus doing in the economy. Because then the Board in 307 00:18:53,000 --> 00:18:57,280 Speaker 1: the monetary policy, they work around the edges. They need 308 00:18:57,320 --> 00:18:59,560 Speaker 1: to know what we think is happening in the economy, 309 00:18:59,600 --> 00:19:02,800 Speaker 1: and part of that is what is Congress doing? And 310 00:19:02,880 --> 00:19:06,800 Speaker 1: so not only did I follow the data in real time, 311 00:19:07,240 --> 00:19:10,040 Speaker 1: I would update my forecast as the data came in. 312 00:19:10,200 --> 00:19:14,760 Speaker 1: This is a very unique UH expertise and experience for 313 00:19:14,840 --> 00:19:18,360 Speaker 1: a macro economist to have. Academics do not do this 314 00:19:18,920 --> 00:19:21,160 Speaker 1: right and people at the board do and I learned 315 00:19:21,280 --> 00:19:25,720 Speaker 1: very well. So in addition to that, I started a 316 00:19:25,760 --> 00:19:30,440 Speaker 1: research program with Matthew Shapiro, who was my advisor at Michigan, 317 00:19:30,960 --> 00:19:34,320 Speaker 1: and Joel Slemrod, who's also a professor there. They had 318 00:19:34,359 --> 00:19:40,119 Speaker 1: a prior research program studying the changes in tax withholding 319 00:19:40,400 --> 00:19:44,159 Speaker 1: the two thousand one rebates they had me joined this product, 320 00:19:44,240 --> 00:19:47,800 Speaker 1: this research program of THEIRS in two thousand eight. We 321 00:19:47,960 --> 00:19:51,080 Speaker 1: did research and ran surveys on the two thousand eight 322 00:19:51,080 --> 00:19:55,160 Speaker 1: tax rebates, the two thousand nine and ten Making Work 323 00:19:55,160 --> 00:19:57,840 Speaker 1: pay tax credit, and the two thousand eleven and two 324 00:19:57,840 --> 00:20:03,440 Speaker 1: thousand twelve payroll tax cut. Fast forward to last year, 325 00:20:03,680 --> 00:20:06,960 Speaker 1: I contributed to a volume called Recession Ready that the 326 00:20:07,000 --> 00:20:10,480 Speaker 1: Hamilton's Project of Brookings and Equitable Growth Right Now Work 327 00:20:11,280 --> 00:20:16,320 Speaker 1: oversaw the volume. I had a chapter on individual payments 328 00:20:16,359 --> 00:20:21,639 Speaker 1: that would happen automatically in a recession. I from my 329 00:20:21,760 --> 00:20:25,760 Speaker 1: expertise that it's got to be big direct payments to 330 00:20:25,840 --> 00:20:30,520 Speaker 1: household This little divvy debby changing with holdings. This is 331 00:20:30,560 --> 00:20:33,440 Speaker 1: not a good way to find a recession. It doesn't 332 00:20:33,440 --> 00:20:36,080 Speaker 1: help families fast enough, and they don't even know what 333 00:20:36,200 --> 00:20:40,399 Speaker 1: happens like still stimulus, Like I don't know much about politics, 334 00:20:40,400 --> 00:20:43,520 Speaker 1: but I know enough to know that probably won't help 335 00:20:43,560 --> 00:20:46,720 Speaker 1: you a lot in terms of saying, you know, Congress, 336 00:20:46,760 --> 00:20:50,040 Speaker 1: the President saying we help the American people. So I 337 00:20:50,080 --> 00:20:56,720 Speaker 1: took my forecasting expertise, my research knowledge, and the research 338 00:20:56,760 --> 00:20:59,000 Speaker 1: knowledge from a lot of other people who work in 339 00:20:59,000 --> 00:21:01,760 Speaker 1: this space. One of the things that the board because 340 00:21:01,800 --> 00:21:04,080 Speaker 1: you don't put your forecast together. You don't walk into 341 00:21:04,119 --> 00:21:07,680 Speaker 1: the boardroom and say, I think this is the right 342 00:21:08,240 --> 00:21:09,919 Speaker 1: thing to do, or this is the right way to 343 00:21:09,920 --> 00:21:13,479 Speaker 1: think about the economy. And here's my research paper, right 344 00:21:13,520 --> 00:21:16,560 Speaker 1: like you come in with here's my paper, here's three 345 00:21:16,560 --> 00:21:20,360 Speaker 1: other papers, here's how they agree, here's how they disagree, 346 00:21:20,880 --> 00:21:23,879 Speaker 1: like and so these were again skills that a lot 347 00:21:23,880 --> 00:21:26,119 Speaker 1: of economists don't have. But that's what I've put into 348 00:21:26,160 --> 00:21:30,720 Speaker 1: my chapter. And in addition, I said, we know the 349 00:21:30,760 --> 00:21:33,960 Speaker 1: two thousand eight in particular, worked really well, like that's 350 00:21:34,000 --> 00:21:37,080 Speaker 1: the way to do it. And and then the add 351 00:21:37,119 --> 00:21:39,159 Speaker 1: on was me thinking about, well, how will we do 352 00:21:39,200 --> 00:21:43,880 Speaker 1: that automatically? And the reason that I had it automatic 353 00:21:44,000 --> 00:21:47,439 Speaker 1: and I had also my proposal in a severe recession, 354 00:21:48,000 --> 00:21:51,400 Speaker 1: not every recession is severe, but in our severe recession, 355 00:21:51,680 --> 00:21:56,560 Speaker 1: those payments would happen automatically on a repeated basis until 356 00:21:56,600 --> 00:22:01,440 Speaker 1: the unemployment rate came down. And that was born out 357 00:22:01,440 --> 00:22:04,120 Speaker 1: of a very painful experience, because I have a very 358 00:22:04,119 --> 00:22:07,000 Speaker 1: emotional reaction to the macro economy. It came from a 359 00:22:07,040 --> 00:22:10,200 Speaker 1: painful experience in two thousand and twelve when the payroll 360 00:22:10,280 --> 00:22:15,400 Speaker 1: tax cut stopped and there wasn't anything else that went 361 00:22:15,440 --> 00:22:19,240 Speaker 1: to a large number of families, and the unemployment rate 362 00:22:19,280 --> 00:22:23,040 Speaker 1: was still high. So I knew from fiscal policy that 363 00:22:23,119 --> 00:22:26,360 Speaker 1: they stepped away. I mean, they're the politicians. I'm not, 364 00:22:26,480 --> 00:22:30,280 Speaker 1: but they made a decision that it was time to 365 00:22:30,320 --> 00:22:33,080 Speaker 1: stop the fiscal relief and in fact they cut back 366 00:22:33,480 --> 00:22:37,280 Speaker 1: on government spending that had a lot of damage the economy. 367 00:22:37,440 --> 00:22:40,879 Speaker 1: Are last recovery was very long, but that's actually a 368 00:22:40,960 --> 00:22:43,640 Speaker 1: bad sign in some ways because it took us so 369 00:22:43,680 --> 00:22:47,679 Speaker 1: long to get the unemployment right down. And that was 370 00:22:47,720 --> 00:22:51,680 Speaker 1: the fiscal policy stepped away, and frankly, monetary policy did 371 00:22:51,720 --> 00:22:55,439 Speaker 1: not step up enough in the recovery. Like they didn't 372 00:22:55,480 --> 00:23:00,840 Speaker 1: save Main Street, they saved Wall Street. There were political 373 00:23:01,080 --> 00:23:05,960 Speaker 1: existential risks to the FED that are why they justified, 374 00:23:06,359 --> 00:23:11,280 Speaker 1: at least internally or in my impression, the like not 375 00:23:11,400 --> 00:23:15,719 Speaker 1: going all in on Main Street. But it it hurts people, right, 376 00:23:15,760 --> 00:23:18,080 Speaker 1: so I knew, like the Fed really can't do this 377 00:23:18,160 --> 00:23:21,879 Speaker 1: in some ways they really shouldn't. But the Congress not 378 00:23:21,960 --> 00:23:24,639 Speaker 1: only can, but they have to. And that is what 379 00:23:24,720 --> 00:23:28,920 Speaker 1: has been so hard right now, Like last week when 380 00:23:29,040 --> 00:23:32,000 Speaker 1: the extra six d a week to the unemployed expired, 381 00:23:33,119 --> 00:23:35,920 Speaker 1: that is going to hurt so many families this year. 382 00:23:36,359 --> 00:23:39,960 Speaker 1: And that program should have been and could have been 383 00:23:40,080 --> 00:23:44,440 Speaker 1: on autopilot, and it was. So let's talking the fallout. 384 00:23:45,600 --> 00:23:49,399 Speaker 1: So let's talk about that program. When Congress passed the 385 00:23:49,480 --> 00:23:54,600 Speaker 1: Cares Act, they sent a check to everybody making I 386 00:23:54,640 --> 00:23:58,760 Speaker 1: think it was less than dollars if memory serves, plus 387 00:23:58,880 --> 00:24:03,720 Speaker 1: five dollars per dependent and then a six hundred dollar 388 00:24:04,960 --> 00:24:09,280 Speaker 1: was that a a weekly or monthly unemployment bonus? How 389 00:24:09,359 --> 00:24:13,720 Speaker 1: much weekly? So? And and that's based roughly on the 390 00:24:13,760 --> 00:24:18,000 Speaker 1: median income across the country. So so that's quite a 391 00:24:18,119 --> 00:24:21,879 Speaker 1: substantial fiscal stimulus or or is it not. What do 392 00:24:21,920 --> 00:24:26,720 Speaker 1: you think of those six hundred plus extending unemployment plus 393 00:24:26,760 --> 00:24:29,840 Speaker 1: five hundred per dependent on a one time check plus 394 00:24:29,880 --> 00:24:32,439 Speaker 1: twelve hundred on a one part check. How would you 395 00:24:32,960 --> 00:24:36,040 Speaker 1: rate that fiscal stimulus and what was the impact in 396 00:24:36,080 --> 00:24:39,119 Speaker 1: the economy in a period where the I think that 397 00:24:39,200 --> 00:24:43,800 Speaker 1: at its worst the Atlanta GDP now then they're now 398 00:24:43,880 --> 00:24:49,000 Speaker 1: casting tool had GDP contracting at fift not on an 399 00:24:49,040 --> 00:24:52,720 Speaker 1: annual basis, but when they happen to take that snapshot 400 00:24:52,840 --> 00:24:57,600 Speaker 1: at the worst part of the economic contraction, the economy 401 00:24:57,640 --> 00:25:02,560 Speaker 1: was effectively cut in half. So I did not sleep 402 00:25:03,080 --> 00:25:05,960 Speaker 1: the night of the vote in the Senate until they 403 00:25:06,000 --> 00:25:09,000 Speaker 1: passed it, which I think men. I stayed up until 404 00:25:09,000 --> 00:25:11,679 Speaker 1: like one am or something the next day. And the 405 00:25:11,800 --> 00:25:14,919 Speaker 1: reason is by the time it got to the Senate, 406 00:25:15,560 --> 00:25:20,439 Speaker 1: I knew this was really good for families and the unemployed. 407 00:25:20,800 --> 00:25:23,680 Speaker 1: I mean, frankly, I was shocked that the six d 408 00:25:23,800 --> 00:25:26,320 Speaker 1: dollars a week made it through, and it almost didn't 409 00:25:26,359 --> 00:25:28,560 Speaker 1: Like the Senate Republicans, there was a group that woke 410 00:25:28,640 --> 00:25:31,160 Speaker 1: up and they're like, that is a lot of money, right, 411 00:25:31,480 --> 00:25:34,800 Speaker 1: and so especially given what the base benefits to the 412 00:25:34,840 --> 00:25:39,840 Speaker 1: unemployed would be now as a macro economist, so setting 413 00:25:39,880 --> 00:25:42,480 Speaker 1: aside how I feel about families and the unemployed as 414 00:25:42,480 --> 00:25:46,760 Speaker 1: a macro economist, this was huge because they passed it 415 00:25:46,920 --> 00:25:50,320 Speaker 1: in March. I mean it took later, longer than the Fed. 416 00:25:50,400 --> 00:25:53,800 Speaker 1: But my goodness for Congress, they really moved right, so 417 00:25:54,040 --> 00:25:58,360 Speaker 1: they moved fast. The rebates I mean, honestly, the rebates 418 00:25:58,400 --> 00:26:00,399 Speaker 1: were better than what I had for a posed in 419 00:26:00,480 --> 00:26:03,880 Speaker 1: my chapter because I didn't think it was possible. They 420 00:26:03,920 --> 00:26:06,840 Speaker 1: are huge. They are twice and I think they should be. 421 00:26:06,880 --> 00:26:10,400 Speaker 1: I'm not saying this was a bad thing. The benefits, 422 00:26:10,480 --> 00:26:13,879 Speaker 1: the relief that went out in these direct payments is 423 00:26:13,960 --> 00:26:18,160 Speaker 1: like twice in generosity what happened in two thousand eight. 424 00:26:18,240 --> 00:26:24,199 Speaker 1: And in addition, the eligibility is expanded. Basically anybody with 425 00:26:24,320 --> 00:26:27,679 Speaker 1: a SO Security number has a claim on those checks. 426 00:26:28,480 --> 00:26:32,360 Speaker 1: And the Treasury did things that sped up the delivery 427 00:26:32,880 --> 00:26:35,880 Speaker 1: relative to two thousand eight. And I mean they said 428 00:26:35,920 --> 00:26:38,239 Speaker 1: up a website where you could go and put your 429 00:26:38,240 --> 00:26:41,679 Speaker 1: payment information in if you hadn't filed taxes. Now, it 430 00:26:41,800 --> 00:26:46,320 Speaker 1: was not perfect. Some people got checked that didn't need them. 431 00:26:46,359 --> 00:26:50,399 Speaker 1: I mean, honestly, a over well over eight of the 432 00:26:50,520 --> 00:26:54,880 Speaker 1: US population, like not even adults, but the population got 433 00:26:54,920 --> 00:27:00,000 Speaker 1: some money from those rebates. That is just like wow. Anyway, 434 00:27:00,200 --> 00:27:02,000 Speaker 1: And the thing is is they got it out fast, 435 00:27:02,320 --> 00:27:05,320 Speaker 1: like the rebates were. In my opinion, the rebates were 436 00:27:05,480 --> 00:27:09,480 Speaker 1: the best administered piece of the entire Cares Act. I'm 437 00:27:09,480 --> 00:27:12,040 Speaker 1: not thinking they were the most important. Like the aid 438 00:27:12,160 --> 00:27:15,440 Speaker 1: that went to the most hurt, like the unemployed, that 439 00:27:15,600 --> 00:27:18,520 Speaker 1: was that's really like, we have to help the people 440 00:27:18,560 --> 00:27:21,320 Speaker 1: who are hurting the most. The thing is, in March, 441 00:27:21,560 --> 00:27:23,520 Speaker 1: we didn't know who was all going to get hurt, 442 00:27:23,840 --> 00:27:26,800 Speaker 1: like the American people were really scared. So it helps. 443 00:27:27,240 --> 00:27:30,440 Speaker 1: And one last thing about the six hundred dollars, there's 444 00:27:30,480 --> 00:27:34,040 Speaker 1: been a lot of discussions that that extra money is 445 00:27:34,080 --> 00:27:37,280 Speaker 1: holding people back from going back to work. I know 446 00:27:37,520 --> 00:27:40,679 Speaker 1: small business owners, even in my own family, who have 447 00:27:40,760 --> 00:27:45,840 Speaker 1: had a difficult time rehiring workers to do work in 448 00:27:46,000 --> 00:27:49,920 Speaker 1: like service industry job because they're like, well, why should 449 00:27:49,960 --> 00:27:52,040 Speaker 1: I go back. I'm getting more every week than I 450 00:27:52,040 --> 00:27:56,720 Speaker 1: would doing your job, and that is legitimate, and yet 451 00:27:57,359 --> 00:28:01,600 Speaker 1: for many many workers, the problem is their employers don't 452 00:28:01,600 --> 00:28:05,040 Speaker 1: need them back because nobody's in the store or not enough. 453 00:28:05,280 --> 00:28:08,640 Speaker 1: And so like that extra money, the unemployed are spending 454 00:28:08,680 --> 00:28:11,600 Speaker 1: it right, and so it is pumping demand in the 455 00:28:11,640 --> 00:28:14,960 Speaker 1: economy that needs it, and it is going away. What 456 00:28:15,040 --> 00:28:17,680 Speaker 1: do you make of the Yale study that said, when 457 00:28:17,720 --> 00:28:20,240 Speaker 1: we look at people who are receiving the six D 458 00:28:20,400 --> 00:28:24,359 Speaker 1: dollar benefit and those who are not, they are both 459 00:28:24,440 --> 00:28:29,359 Speaker 1: returning back to the workforce in the same numbers. So 460 00:28:29,520 --> 00:28:34,800 Speaker 1: at this point there are various research studies and and 461 00:28:34,840 --> 00:28:37,879 Speaker 1: this is this is coming from academics, this is coming 462 00:28:37,920 --> 00:28:42,480 Speaker 1: from policy analysts. I've done work in this space. Also 463 00:28:42,720 --> 00:28:47,280 Speaker 1: that that money that support is mattering and it is 464 00:28:47,400 --> 00:28:52,080 Speaker 1: not holding back the economy. Now, there will be a point, 465 00:28:52,560 --> 00:28:55,360 Speaker 1: in my expert opinion, as the unemployment rate comes down 466 00:28:55,400 --> 00:28:58,880 Speaker 1: and jobs become more plentiful, that we should think hard 467 00:28:58,920 --> 00:29:02,240 Speaker 1: about our were paying are not paying? Are we giving 468 00:29:02,280 --> 00:29:06,560 Speaker 1: people more money than they normally would have gotten? The 469 00:29:06,720 --> 00:29:09,160 Speaker 1: very important piece out of the study I saw it 470 00:29:09,320 --> 00:29:12,160 Speaker 1: yesterday that I'm sorry, I'm not going to attribute it correctly, 471 00:29:12,680 --> 00:29:17,680 Speaker 1: but they showed that in past recessions what enhanced benefits, 472 00:29:17,680 --> 00:29:19,800 Speaker 1: and in that case it was the extended durations being 473 00:29:19,800 --> 00:29:22,280 Speaker 1: able to stay on longer than twenty six weeks. It 474 00:29:22,440 --> 00:29:25,480 Speaker 1: showed that it allowed people the time to go get 475 00:29:25,520 --> 00:29:29,280 Speaker 1: a job again that was commensurate with their skills, and 476 00:29:29,360 --> 00:29:34,120 Speaker 1: that was particularly important for people in disadvantaged groups, so 477 00:29:34,200 --> 00:29:38,040 Speaker 1: people of color, the less educated, and women. So we 478 00:29:38,160 --> 00:29:40,960 Speaker 1: don't want people to go back too fast because they'll 479 00:29:41,000 --> 00:29:42,840 Speaker 1: get in jobs that aren't the right jobs for them. 480 00:29:42,880 --> 00:29:44,920 Speaker 1: And right now, oh my goodness, a lot of these 481 00:29:44,960 --> 00:29:47,600 Speaker 1: jobs are not safe. So we want to make sure 482 00:29:48,200 --> 00:29:51,280 Speaker 1: that we don't kill people. Right So there's six hundred 483 00:29:51,320 --> 00:29:55,040 Speaker 1: dollars right now, makes a lot of sense reasonable people. 484 00:29:55,280 --> 00:29:58,000 Speaker 1: When we get five years into this and unemployment rate 485 00:29:58,040 --> 00:30:01,480 Speaker 1: of six percent, then let's talked about it. And I 486 00:30:01,480 --> 00:30:04,360 Speaker 1: am in the group that thinks we should phase it 487 00:30:04,400 --> 00:30:09,720 Speaker 1: down automatically as the unemployment rate comes down. Oh, I 488 00:30:09,800 --> 00:30:12,520 Speaker 1: like the idea of using a metric to UH to 489 00:30:12,640 --> 00:30:16,680 Speaker 1: make that determination and taking it out of the political realm. 490 00:30:16,880 --> 00:30:22,200 Speaker 1: Last question on unemployment and these fiscal stimulus in these checks. 491 00:30:22,760 --> 00:30:26,600 Speaker 1: We're recording this in the first weekend of August. There 492 00:30:26,880 --> 00:30:31,240 Speaker 1: is no deal yet for the Cares Act renewal. What 493 00:30:31,360 --> 00:30:35,360 Speaker 1: do you think would be appropriate for Congress to pass 494 00:30:36,040 --> 00:30:40,840 Speaker 1: relative to unemployment and another one off check or not. 495 00:30:43,080 --> 00:30:47,160 Speaker 1: I want Congress to pass a new relief package that 496 00:30:47,280 --> 00:30:51,680 Speaker 1: is between four and six trillion dollars. I am not 497 00:30:51,960 --> 00:30:55,440 Speaker 1: expecting to get that. I truly believe, in my expert 498 00:30:55,440 --> 00:30:59,840 Speaker 1: opinion that they need to go big again and they 499 00:31:00,040 --> 00:31:02,840 Speaker 1: need to do what works. So I just I want 500 00:31:02,920 --> 00:31:05,160 Speaker 1: Treasure to just push the button again and send out 501 00:31:05,160 --> 00:31:09,520 Speaker 1: those checks we would have for people who have direct deposits. 502 00:31:09,640 --> 00:31:13,080 Speaker 1: They would have that money within a week of Congress 503 00:31:13,120 --> 00:31:16,239 Speaker 1: approving it because the heavy lifting of putting together a 504 00:31:16,280 --> 00:31:19,440 Speaker 1: file of who gets the check, where's their bank account? 505 00:31:20,080 --> 00:31:23,080 Speaker 1: That file exists. So if you do it exactly like 506 00:31:23,160 --> 00:31:27,040 Speaker 1: you did last time, it goes really fat. So yeah, 507 00:31:27,440 --> 00:31:32,840 Speaker 1: that is good. I want to see the unemployment benefits continue, 508 00:31:33,000 --> 00:31:35,680 Speaker 1: just like I said, tie them to the economy, keep 509 00:31:35,720 --> 00:31:38,640 Speaker 1: them where they are right now. Especially the six dollars 510 00:31:38,720 --> 00:31:41,480 Speaker 1: is so big because when the Cares Act was past, 511 00:31:41,560 --> 00:31:45,200 Speaker 1: we were in a pandemic. We did not expect to 512 00:31:45,240 --> 00:31:48,160 Speaker 1: be in a pandemic now, but we are now. I 513 00:31:48,360 --> 00:31:50,600 Speaker 1: know from having I've been doing a lot of work 514 00:31:50,640 --> 00:31:53,240 Speaker 1: with a lot of different offices and members in Congress. 515 00:31:53,360 --> 00:31:55,280 Speaker 1: That's why I left the FED. Couldn't do that when 516 00:31:55,280 --> 00:31:58,800 Speaker 1: I was there. I spent Mother's Day weekend putting together 517 00:31:58,880 --> 00:32:03,520 Speaker 1: a cost estimate for the unemployment insurance, the enhanced benefits 518 00:32:03,520 --> 00:32:07,080 Speaker 1: time to the unemployment rate. Doing forecasters. I mean, there's 519 00:32:07,080 --> 00:32:08,800 Speaker 1: something I learned how to do it defense there are 520 00:32:08,840 --> 00:32:10,520 Speaker 1: not a lot of people that know how to do this, 521 00:32:11,160 --> 00:32:13,720 Speaker 1: and I came out with an estimate that was about 522 00:32:13,960 --> 00:32:17,000 Speaker 1: it was a little over two trillion. And the expensive 523 00:32:17,040 --> 00:32:20,440 Speaker 1: part of that is Congressional Budget Office and a lot 524 00:32:20,480 --> 00:32:25,360 Speaker 1: of forecasters think this is going to take a long time, right, 525 00:32:25,440 --> 00:32:27,920 Speaker 1: so the phase down of those benefits is going to 526 00:32:27,960 --> 00:32:30,720 Speaker 1: happen slowly, and that puts the big price tag on 527 00:32:31,200 --> 00:32:34,920 Speaker 1: Now the CBO, the Congressional Budget Office, doesn't do the 528 00:32:34,960 --> 00:32:37,480 Speaker 1: feedback effects. I think in the end it would really 529 00:32:37,520 --> 00:32:42,320 Speaker 1: cost the cost taxpayers less than two trillions because we 530 00:32:42,400 --> 00:32:45,120 Speaker 1: get the economy going faster. But at the end of 531 00:32:45,120 --> 00:32:47,360 Speaker 1: the day, that's one reason it's a big ticket. One 532 00:32:47,400 --> 00:32:50,640 Speaker 1: more I'll say that I think is really important. Wait 533 00:32:50,680 --> 00:32:53,800 Speaker 1: before you move past that point, I just have to say, 534 00:32:54,760 --> 00:33:00,760 Speaker 1: you're describing the sort of supply side unemployment benefit where 535 00:33:01,000 --> 00:33:05,400 Speaker 1: it's cheaper than it looks because its own economic activity 536 00:33:05,600 --> 00:33:07,920 Speaker 1: is going to help pay for itself. Is that what 537 00:33:08,000 --> 00:33:13,200 Speaker 1: you're saying that's right. Well, in a wonky world, they 538 00:33:13,280 --> 00:33:17,800 Speaker 1: call this dynamic scoring, where Congressional Budget Office would take 539 00:33:17,800 --> 00:33:21,160 Speaker 1: into account of feedback. In this case, relief has positive 540 00:33:21,160 --> 00:33:27,640 Speaker 1: feedback effects definitely now. Right now, the Congressional Budget Office 541 00:33:27,680 --> 00:33:32,480 Speaker 1: can only do that kind of analysis for changes in taxes. 542 00:33:33,280 --> 00:33:37,160 Speaker 1: There's just something Congress decided. So you know, we can't 543 00:33:37,240 --> 00:33:39,959 Speaker 1: run this through and expect to get back a smaller score. 544 00:33:40,480 --> 00:33:43,440 Speaker 1: I have to make the argument, and others have that 545 00:33:43,600 --> 00:33:46,880 Speaker 1: we know it will help the economy. And if we 546 00:33:46,960 --> 00:33:49,680 Speaker 1: help the economy right now, it is a down payment 547 00:33:50,200 --> 00:33:53,840 Speaker 1: on the next few years being a lot better than 548 00:33:53,920 --> 00:33:57,560 Speaker 1: they look like they're headed to be. So let's talk 549 00:33:57,600 --> 00:34:00,800 Speaker 1: about the some rule a bit. When the three month 550 00:34:01,080 --> 00:34:06,720 Speaker 1: moving average of unemployment moves above its previous low, you 551 00:34:06,800 --> 00:34:11,400 Speaker 1: say we're in recession. Tell us why that is. So, 552 00:34:11,920 --> 00:34:15,799 Speaker 1: it's just it's an empirical regularity, right. I spent a 553 00:34:15,800 --> 00:34:19,000 Speaker 1: lot of time with a spreadsheet over weekends. Again, this 554 00:34:19,080 --> 00:34:22,040 Speaker 1: was in part to do my proposal of automatic payments 555 00:34:22,080 --> 00:34:24,400 Speaker 1: to people like you gotta know when to send out 556 00:34:24,480 --> 00:34:27,879 Speaker 1: hundreds of billions of dollars, right, You don't particularly want 557 00:34:27,920 --> 00:34:31,360 Speaker 1: to mess that up. And I knew, and this is 558 00:34:31,400 --> 00:34:35,879 Speaker 1: a principle that Federal Reserve economists, no people on Wall 559 00:34:36,000 --> 00:34:40,399 Speaker 1: Street know that a small increase in the unemployment rate 560 00:34:40,600 --> 00:34:44,480 Speaker 1: is a bad sign. Now, I wanted to really understand 561 00:34:44,800 --> 00:34:49,600 Speaker 1: when it's accurate and when it's in a recession. The 562 00:34:49,600 --> 00:34:53,040 Speaker 1: Federal Reserve has a rule of thumb, which I did check. 563 00:34:53,080 --> 00:34:55,480 Speaker 1: After they called this assomb rule. I asked one of 564 00:34:55,480 --> 00:34:58,040 Speaker 1: my former bosses. I'm like, did I scoop the board's rule? 565 00:34:58,160 --> 00:35:00,840 Speaker 1: Like I do not want to, because we'll rename it 566 00:35:00,840 --> 00:35:03,319 Speaker 1: will be the FED rule, right, And he said no. 567 00:35:03,960 --> 00:35:07,280 Speaker 1: The internal rules the FED was a three tents increase 568 00:35:07,600 --> 00:35:12,600 Speaker 1: in the unemployment rate, and that happens ahead of recessions. 569 00:35:12,800 --> 00:35:15,800 Speaker 1: And I know one time in two thousands three, because 570 00:35:15,800 --> 00:35:17,960 Speaker 1: I tried everything under the sun when I came up 571 00:35:17,960 --> 00:35:20,120 Speaker 1: with my rule, that it triggered and it was a 572 00:35:20,120 --> 00:35:23,920 Speaker 1: false positive, right, because that small increase happened in that 573 00:35:24,000 --> 00:35:27,239 Speaker 1: jobless recovery, it didn't end up being considered a recession. 574 00:35:27,880 --> 00:35:29,880 Speaker 1: So three tents was the rule. It makes sense for 575 00:35:29,920 --> 00:35:33,239 Speaker 1: the FED because monetary policy wants to get ahead of 576 00:35:33,239 --> 00:35:36,880 Speaker 1: the game if it can, because it often is believed 577 00:35:36,880 --> 00:35:38,560 Speaker 1: that it acts with the lags you know, if you're 578 00:35:38,719 --> 00:35:41,920 Speaker 1: lowering interest rates, and frankly, if they cut a quarter 579 00:35:41,960 --> 00:35:44,640 Speaker 1: point and it is an actually a recession, like they'll 580 00:35:44,680 --> 00:35:47,120 Speaker 1: pat themselves on the back and it's not like, you know, 581 00:35:47,160 --> 00:35:50,560 Speaker 1: taxpayers have just lost three hundred billion dollars of their money, 582 00:35:50,640 --> 00:35:54,759 Speaker 1: quote unquote. So I had a different goal because mine 583 00:35:54,840 --> 00:35:58,160 Speaker 1: was about what Congress does. And so I found a 584 00:35:58,239 --> 00:36:02,920 Speaker 1: rule that always triggered within the first few months of 585 00:36:02,920 --> 00:36:08,120 Speaker 1: a recession. And I also believe that the indicator I 586 00:36:08,280 --> 00:36:11,880 Speaker 1: use is such a good one because it is the 587 00:36:12,000 --> 00:36:15,759 Speaker 1: reason that we hate recessions and we fight back. It 588 00:36:15,920 --> 00:36:20,759 Speaker 1: is people losing their jobs. Those people, especially in a recession, 589 00:36:21,320 --> 00:36:23,359 Speaker 1: especially if it takes well to get a new job, 590 00:36:23,760 --> 00:36:26,920 Speaker 1: they will pay for that in terms of their careers 591 00:36:26,960 --> 00:36:29,919 Speaker 1: and their families will pay for it for a very 592 00:36:30,000 --> 00:36:33,759 Speaker 1: long time. So to me, it's a widely followed statistic. 593 00:36:33,960 --> 00:36:37,080 Speaker 1: It makes a lot of sense. It's a federal reserve. 594 00:36:37,120 --> 00:36:40,880 Speaker 1: They also use things called regimes switching factor models. I 595 00:36:40,880 --> 00:36:43,279 Speaker 1: am not taking that to Congress, like, this is not 596 00:36:43,400 --> 00:36:45,759 Speaker 1: what you want to have, you know, money, but at 597 00:36:45,760 --> 00:36:47,840 Speaker 1: a futtal reserve. I mean, you ought to use everything 598 00:36:47,920 --> 00:36:51,719 Speaker 1: under the sun to understand the macro economy. You have 599 00:36:51,880 --> 00:36:54,799 Speaker 1: to have a simple rule if you want to put 600 00:36:55,200 --> 00:36:58,680 Speaker 1: fiscal policy on autopilot. So to me, it was a 601 00:36:58,719 --> 00:37:01,759 Speaker 1: great rule in my chap her is called a recession indicator. 602 00:37:01,800 --> 00:37:03,480 Speaker 1: When I showed up at the launch event for the 603 00:37:03,520 --> 00:37:06,120 Speaker 1: book and they started calling the somb rule, I was 604 00:37:06,200 --> 00:37:11,000 Speaker 1: very uncomfortable, and to the point that after the event, 605 00:37:11,080 --> 00:37:13,200 Speaker 1: I went and talked to Christie Romer. I wanted to 606 00:37:13,200 --> 00:37:15,680 Speaker 1: talk to her about some physcal stimula. She was one 607 00:37:15,719 --> 00:37:19,160 Speaker 1: of the main panelists, and I said, I'm so uncomfortable 608 00:37:19,200 --> 00:37:21,400 Speaker 1: with the som rule thing. And she looked at me 609 00:37:21,440 --> 00:37:23,960 Speaker 1: and she's like, Claudia, you have got to own this. 610 00:37:24,480 --> 00:37:27,960 Speaker 1: Any man would And I was like, okay, Christie is 611 00:37:28,000 --> 00:37:30,720 Speaker 1: my hero. I would listen to Christie what I learned 612 00:37:30,760 --> 00:37:33,400 Speaker 1: Since then, and I've joked a little bit about this 613 00:37:33,440 --> 00:37:38,120 Speaker 1: and ribbed some people online like Bill Dudley that owning 614 00:37:38,160 --> 00:37:41,760 Speaker 1: it actually meant I had to defend it, right, because again, 615 00:37:42,160 --> 00:37:44,640 Speaker 1: this principle is there and it was great and it 616 00:37:44,719 --> 00:37:48,480 Speaker 1: was important for me to understand like the intellectual history 617 00:37:48,520 --> 00:37:52,200 Speaker 1: of it. But like I already did um anyways, but 618 00:37:52,280 --> 00:37:54,880 Speaker 1: I am thrilled and I always tell the people that 619 00:37:54,960 --> 00:37:57,440 Speaker 1: are like, oh, well, we knew this and that that, 620 00:37:57,520 --> 00:37:59,879 Speaker 1: And I was like, but if everybody in the world 621 00:38:00,040 --> 00:38:03,600 Speaker 1: new it, it wouldn't be in the Bloomberg terminals, in 622 00:38:03,719 --> 00:38:08,240 Speaker 1: haveor in Fred's with my name. So maybe I wasn't 623 00:38:08,600 --> 00:38:11,759 Speaker 1: like the person who thought the big thought. I think 624 00:38:11,840 --> 00:38:14,799 Speaker 1: I did not think the big thoughts, and yet I 625 00:38:14,880 --> 00:38:18,000 Speaker 1: got it out to the world. And to me, that's important. 626 00:38:18,000 --> 00:38:21,120 Speaker 1: And I've spent a lot of time with Congress trying 627 00:38:21,160 --> 00:38:24,400 Speaker 1: to help them understand why this is such a good 628 00:38:24,440 --> 00:38:28,080 Speaker 1: thing to do. So let me let me push back 629 00:38:28,280 --> 00:38:32,279 Speaker 1: on your um false modesty, I'll call it. There was 630 00:38:32,280 --> 00:38:35,279 Speaker 1: a Wall Street Art Wall Street Journal article. I love 631 00:38:35,360 --> 00:38:39,960 Speaker 1: this headline quote, are we in a recession? Experts agree? 632 00:38:40,480 --> 00:38:45,960 Speaker 1: Ask Claudius some So that is quite a m accolade 633 00:38:46,000 --> 00:38:48,320 Speaker 1: in the journal. I would have that on my wall 634 00:38:48,560 --> 00:38:52,240 Speaker 1: in my office. What sort of pushback did you get 635 00:38:52,719 --> 00:38:58,040 Speaker 1: to that that article? And I'm curious was it intellectual 636 00:38:58,239 --> 00:39:01,799 Speaker 1: pushback to the idea or was it pushed back to 637 00:39:02,440 --> 00:39:09,440 Speaker 1: who really owned authorship of it? So when I saw 638 00:39:09,480 --> 00:39:14,560 Speaker 1: that article and I was thrilled. Kate Davidson has been 639 00:39:14,640 --> 00:39:19,640 Speaker 1: such a booster of my career. So the response to 640 00:39:19,719 --> 00:39:22,959 Speaker 1: that well even my response when I when I saw 641 00:39:23,000 --> 00:39:27,880 Speaker 1: the headline is I was like, if you asked settle 642 00:39:27,920 --> 00:39:31,920 Speaker 1: reserved staff economists, I would not be the names that 643 00:39:32,040 --> 00:39:35,719 Speaker 1: they would bring out, right like, and I knew that, 644 00:39:35,760 --> 00:39:37,799 Speaker 1: and I knew it because you know, months before is 645 00:39:37,840 --> 00:39:41,239 Speaker 1: when the somber was born, and you know there had 646 00:39:41,280 --> 00:39:45,640 Speaker 1: been some attention to it. Like I just had people 647 00:39:45,760 --> 00:39:48,560 Speaker 1: that were really clear and not in a like mean way. 648 00:39:48,760 --> 00:39:53,839 Speaker 1: But there's the board is a very interesting place. There 649 00:39:53,840 --> 00:39:56,560 Speaker 1: are times and the summer was an example of many 650 00:39:57,080 --> 00:39:59,799 Speaker 1: the things that I know about the macro economy I 651 00:40:00,080 --> 00:40:02,799 Speaker 1: learned at the FED. Like it's it's the board right 652 00:40:02,800 --> 00:40:06,960 Speaker 1: where this kind of brain that passes along macro. Now 653 00:40:07,719 --> 00:40:09,719 Speaker 1: that meant that when I spoke out and this had 654 00:40:09,760 --> 00:40:12,000 Speaker 1: happened on Twitter, so I knew this was an issue. 655 00:40:12,640 --> 00:40:16,280 Speaker 1: It's like, well, it's not fair you get the credit 656 00:40:16,600 --> 00:40:20,160 Speaker 1: because you're speaking out and you learned it from everybody. 657 00:40:20,840 --> 00:40:25,200 Speaker 1: And I tried always be cognizant of that and give 658 00:40:25,239 --> 00:40:28,200 Speaker 1: credit where credit is due. Part of where credit is 659 00:40:28,280 --> 00:40:30,879 Speaker 1: due is with me, Like I'm the one that spent 660 00:40:30,960 --> 00:40:36,640 Speaker 1: weekends with this spreadsheet. I had someone contact me after, 661 00:40:37,080 --> 00:40:40,279 Speaker 1: you know, a friend, it's a FED contact me afterwards, 662 00:40:40,320 --> 00:40:43,600 Speaker 1: and he was like, so the spreadsheet, she said, it 663 00:40:43,640 --> 00:40:46,480 Speaker 1: was this massive spreadsheet. Seriously, this rule is so simple. 664 00:40:46,880 --> 00:40:49,759 Speaker 1: And I looked at him and I said, well, I 665 00:40:49,960 --> 00:40:52,719 Speaker 1: pulled all the real time data, which means that I 666 00:40:52,760 --> 00:40:55,160 Speaker 1: looked at all the data as people saw it at 667 00:40:55,200 --> 00:40:59,799 Speaker 1: that time, which is more complicated. And frankly, this man, 668 00:41:00,000 --> 00:41:03,760 Speaker 1: who I truly think as an amazing economist, he works 669 00:41:03,760 --> 00:41:06,920 Speaker 1: on the financial side of the FED. I work on 670 00:41:06,960 --> 00:41:09,279 Speaker 1: the real side. If I had asked him to do 671 00:41:09,360 --> 00:41:11,960 Speaker 1: the real time analysis, it would have taken him a 672 00:41:12,000 --> 00:41:15,160 Speaker 1: long time, right, But those are the kind of like, oh, 673 00:41:15,239 --> 00:41:18,200 Speaker 1: this is so simple. And it wasn't saying that I 674 00:41:18,239 --> 00:41:22,400 Speaker 1: didn't deserve it so much as we all deserved it, 675 00:41:22,760 --> 00:41:26,400 Speaker 1: like the whole staff, and like the staff from years before, 676 00:41:27,000 --> 00:41:31,359 Speaker 1: and you know, like as with Twitter, I I take 677 00:41:31,440 --> 00:41:35,600 Speaker 1: the risk of speaking out. So I don't know, but 678 00:41:35,680 --> 00:41:38,440 Speaker 1: I was used to this and I wasn't surprised. And honestly, 679 00:41:38,960 --> 00:41:41,040 Speaker 1: if I hadn't have been a FED forecaster, if I 680 00:41:41,080 --> 00:41:43,600 Speaker 1: hadn't spent a year at c A where finally early 681 00:41:43,640 --> 00:41:48,239 Speaker 1: in twenty six things were wobbly, right, so um and 682 00:41:48,320 --> 00:41:50,360 Speaker 1: I actually at the event tried to give the credit 683 00:41:50,400 --> 00:41:53,200 Speaker 1: off to Jason Furman, who then said, oh the fight, 684 00:41:53,280 --> 00:41:55,600 Speaker 1: this is more like Doug Elmendorff. And then Christie's like, 685 00:41:55,719 --> 00:41:59,200 Speaker 1: you have to stop, like this is you um anyway? 686 00:41:59,280 --> 00:42:04,080 Speaker 1: So it's interesting experience. I'm not really like, is this 687 00:42:04,160 --> 00:42:07,480 Speaker 1: a peculiarity of the FED? And what bothers me the 688 00:42:07,640 --> 00:42:11,200 Speaker 1: most about it is we knew. It's like the FED 689 00:42:11,520 --> 00:42:14,759 Speaker 1: knew for a long time. And what happened is when 690 00:42:14,800 --> 00:42:17,920 Speaker 1: I heard it with the world, the world didn't know. 691 00:42:20,280 --> 00:42:23,839 Speaker 1: Now that's quite that's quite interesting. If let me ask 692 00:42:23,880 --> 00:42:26,640 Speaker 1: you this question as an author, and I'll get off 693 00:42:26,680 --> 00:42:31,279 Speaker 1: of the some rule after this, was anyone in the 694 00:42:31,320 --> 00:42:37,280 Speaker 1: FED using the rule of thumb, three month average jobless 695 00:42:37,360 --> 00:42:40,600 Speaker 1: rate rising half a percent from a previous twelve month low? 696 00:42:41,040 --> 00:42:45,000 Speaker 1: Was that anywhere um on any FED sheets before you 697 00:42:45,040 --> 00:42:51,719 Speaker 1: publicized it in that format and with that conclusion no, 698 00:42:53,080 --> 00:42:59,399 Speaker 1: So then then then you get the authorship is the 699 00:42:59,400 --> 00:43:03,160 Speaker 1: principle there's no principle. There's no principle. The principle is 700 00:43:03,239 --> 00:43:07,840 Speaker 1: you wrote it, you created it. I'm I'm listen, you 701 00:43:07,840 --> 00:43:09,719 Speaker 1: know I'm gonna say this. I might as well say 702 00:43:09,719 --> 00:43:11,680 Speaker 1: it on the record instead of saying off the record. 703 00:43:11,880 --> 00:43:15,560 Speaker 1: When I first started blogging in the nineties and then 704 00:43:15,560 --> 00:43:18,640 Speaker 1: in the early two thousands, I was a guest. How 705 00:43:18,680 --> 00:43:21,960 Speaker 1: frequently I would write something on a blog and then 706 00:43:22,160 --> 00:43:24,520 Speaker 1: weeks later or a days later, see it show up 707 00:43:24,520 --> 00:43:29,440 Speaker 1: in a mainstream paper with no credit, no link, no citation, 708 00:43:30,040 --> 00:43:32,560 Speaker 1: just oh you like that idea? What do you think? 709 00:43:32,600 --> 00:43:35,279 Speaker 1: I'm your writing staff, I'm I'm I'm punching up your 710 00:43:35,760 --> 00:43:38,960 Speaker 1: your script. You just stole this. I mean sometimes it 711 00:43:39,040 --> 00:43:42,280 Speaker 1: was word for word. So I think if you create 712 00:43:42,360 --> 00:43:46,000 Speaker 1: something that has not been created before, even if other 713 00:43:46,040 --> 00:43:49,319 Speaker 1: people contribute to it, hey we're we're all standing on 714 00:43:49,360 --> 00:43:53,279 Speaker 1: the shoulders of giants. You were entitled to the to 715 00:43:53,400 --> 00:43:58,200 Speaker 1: the authorship credit not hereby deem the som rule. Officially yours. 716 00:43:58,640 --> 00:44:01,439 Speaker 1: I have that authority because I'm on the radio. Let's 717 00:44:01,440 --> 00:44:04,120 Speaker 1: talk about a fiery blog post you wrote a couple 718 00:44:04,160 --> 00:44:09,239 Speaker 1: of weeks ago titled economics is a disgrace, And I'm 719 00:44:09,239 --> 00:44:13,280 Speaker 1: going to suggest listeners go to macro mom and find 720 00:44:13,640 --> 00:44:17,080 Speaker 1: that blog post and it you make a number of 721 00:44:17,640 --> 00:44:23,600 Speaker 1: really interesting allegations, the first of which is economics research 722 00:44:23,920 --> 00:44:29,839 Speaker 1: replicable sixty published papers from thirteen generals say usually not 723 00:44:30,600 --> 00:44:35,680 Speaker 1: these various research papers were only able to replicate about 724 00:44:35,719 --> 00:44:40,520 Speaker 1: a third of previous research that was published in various 725 00:44:40,560 --> 00:44:46,200 Speaker 1: economic journals. What's wrong with the state of economic research today? 726 00:44:46,520 --> 00:44:49,960 Speaker 1: It says a lot of things about the field of research. 727 00:44:51,080 --> 00:44:55,160 Speaker 1: One that I didn't touch on in my blog post 728 00:44:56,120 --> 00:45:01,160 Speaker 1: is it it shows that we don't have a culture 729 00:45:01,880 --> 00:45:06,600 Speaker 1: of going back and checking each other's work, right I. 730 00:45:07,280 --> 00:45:10,080 Speaker 1: And there was pushback, and I'll come back to this 731 00:45:10,239 --> 00:45:14,080 Speaker 1: about the paper, because it wasn't like they went and 732 00:45:14,120 --> 00:45:16,919 Speaker 1: did like a news study. You know, like I work 733 00:45:16,960 --> 00:45:20,720 Speaker 1: in consumer spending. I have written so many papers showing 734 00:45:20,760 --> 00:45:25,359 Speaker 1: falsification of a basic principle of consumer spending models, as 735 00:45:25,400 --> 00:45:28,120 Speaker 1: as like hundreds of other people. Right, So it's not 736 00:45:28,200 --> 00:45:31,000 Speaker 1: like someone's checking my work where I'm not checking Jonathan 737 00:45:31,000 --> 00:45:35,200 Speaker 1: Parker's work. We're just doing different studies. What this paper 738 00:45:35,360 --> 00:45:38,920 Speaker 1: by Andrew Chang and Philip Lee did is they said, Okay, 739 00:45:39,080 --> 00:45:41,399 Speaker 1: let's go to the top journals and let's just see 740 00:45:41,400 --> 00:45:44,279 Speaker 1: if we can get their main results. They weren't even 741 00:45:44,320 --> 00:45:46,960 Speaker 1: trying to replicate all the results. They just wanted the 742 00:45:47,000 --> 00:45:55,879 Speaker 1: main takeaway empirical results of the finding. And they they 743 00:45:56,080 --> 00:45:59,200 Speaker 1: did this in a way Andrew Kang was a colleague 744 00:45:59,239 --> 00:46:01,799 Speaker 1: of mine. For you is at the Federal Reserve. He 745 00:46:02,000 --> 00:46:06,319 Speaker 1: is an absolutely industrious person, not as fire as me, 746 00:46:06,640 --> 00:46:12,680 Speaker 1: like he's more soft spoken. He completely rolled up his sleeves. 747 00:46:12,760 --> 00:46:16,000 Speaker 1: He had an army practically of research assistance. He was 748 00:46:16,040 --> 00:46:20,080 Speaker 1: also in the macro forecasting section with me, and they 749 00:46:20,120 --> 00:46:25,880 Speaker 1: spent hundreds of hours on this project. They were so careful, 750 00:46:26,200 --> 00:46:28,720 Speaker 1: like there were no cutting corners, there was no playing 751 00:46:28,760 --> 00:46:32,640 Speaker 1: fast and loose. They wanted to be able to replicate. 752 00:46:33,680 --> 00:46:37,160 Speaker 1: They put a lot of time into it, and it 753 00:46:37,239 --> 00:46:40,560 Speaker 1: should have been a finding that we as a profession 754 00:46:40,880 --> 00:46:46,120 Speaker 1: took really seriously. And instead from very elite members of 755 00:46:46,160 --> 00:46:52,680 Speaker 1: the profession they were they were received with derision. I 756 00:46:52,680 --> 00:46:58,480 Speaker 1: mean they were outright criticized, put down in public. The 757 00:46:58,520 --> 00:47:01,680 Speaker 1: paper was death rejected it. In addition, where I talked 758 00:47:01,680 --> 00:47:04,279 Speaker 1: about in the blog post, Andrew shared with me a 759 00:47:04,360 --> 00:47:07,920 Speaker 1: correspondence that he received from a very senior person in 760 00:47:07,960 --> 00:47:10,160 Speaker 1: the profession because he knew I had had problems with 761 00:47:10,280 --> 00:47:14,560 Speaker 1: this person. And I was furious, but I told Andrew, 762 00:47:15,120 --> 00:47:18,840 Speaker 1: this man does it, but it is absolutely unacceptable. The 763 00:47:18,880 --> 00:47:21,520 Speaker 1: paper was rejected at all the top journals. It did 764 00:47:21,560 --> 00:47:24,560 Speaker 1: finally find a home and adding injury to insults in 765 00:47:24,600 --> 00:47:28,040 Speaker 1: one of those top journals. Another researcher, much more prominent, 766 00:47:28,680 --> 00:47:32,600 Speaker 1: published a paper later saying we should do more replication. 767 00:47:33,200 --> 00:47:35,400 Speaker 1: I mean, it was just it was astounding to me 768 00:47:35,640 --> 00:47:39,360 Speaker 1: on so many different levels of this elitism and the 769 00:47:39,400 --> 00:47:45,239 Speaker 1: profession pushing back on uncomfortable conversations, and then like, we 770 00:47:45,360 --> 00:47:49,160 Speaker 1: actually need a culture of replication, Like I know that 771 00:47:49,320 --> 00:47:53,040 Speaker 1: is a policy analyst. I never took a result, a 772 00:47:53,040 --> 00:47:55,800 Speaker 1: piece of advice into the boardroom that was one paper, 773 00:47:56,160 --> 00:47:58,360 Speaker 1: especially if it was some paper that was like totally 774 00:47:58,360 --> 00:48:02,200 Speaker 1: different than every other paper written on the topic. Academia 775 00:48:02,760 --> 00:48:08,840 Speaker 1: rewards novel surprising findings. Those are the ones that we 776 00:48:09,040 --> 00:48:13,040 Speaker 1: absolutely should be checking the map, right, because I'm not 777 00:48:13,080 --> 00:48:15,680 Speaker 1: saying they're all wrong, but I mean Andrew and Phillips 778 00:48:15,719 --> 00:48:19,600 Speaker 1: research showed yeah, you should really, we should really do 779 00:48:19,719 --> 00:48:23,480 Speaker 1: more of this, and and we don't economics and frankly 780 00:48:23,880 --> 00:48:27,960 Speaker 1: his paper, their paper was ignored. Let me push back 781 00:48:28,000 --> 00:48:31,279 Speaker 1: a little bit against your argument with a quote from 782 00:48:31,440 --> 00:48:36,360 Speaker 1: famous physicist Max Planck, basically saying, what the old guard 783 00:48:36,400 --> 00:48:38,960 Speaker 1: believes doesn't go away until the old guard is dead. 784 00:48:39,440 --> 00:48:43,200 Speaker 1: So how is economics any different from physics? Or other 785 00:48:43,320 --> 00:48:49,120 Speaker 1: fields where you have this entrenched, calcified belief system that 786 00:48:49,400 --> 00:48:53,520 Speaker 1: literally takes a generation to get past. So when I 787 00:48:53,600 --> 00:48:56,480 Speaker 1: hear the quote now, and I've heard it in the past, 788 00:48:56,560 --> 00:48:59,080 Speaker 1: and I agree with it, and I think the direction 789 00:48:59,120 --> 00:49:05,439 Speaker 1: you're going. But a few weeks ago, Emmanuel Fari, who 790 00:49:05,520 --> 00:49:12,640 Speaker 1: is a forty one year old brilliant macro economists really 791 00:49:12,680 --> 00:49:15,520 Speaker 1: pushing the boundaries of the field in a very good way, 792 00:49:15,680 --> 00:49:19,040 Speaker 1: and a kind man and a mentor too many he 793 00:49:19,280 --> 00:49:23,880 Speaker 1: killed himself, and in the last four years Marty Weisman 794 00:49:24,000 --> 00:49:29,560 Speaker 1: killed himself, and Alan Krueger and build Standholme, And these 795 00:49:29,640 --> 00:49:33,520 Speaker 1: are people who are creative. They were trying to change 796 00:49:33,520 --> 00:49:36,719 Speaker 1: the field, both in the way we treat people and 797 00:49:36,719 --> 00:49:39,040 Speaker 1: in the things that we think and explore and the 798 00:49:39,200 --> 00:49:44,200 Speaker 1: questions and the findings. And to me that that shows 799 00:49:44,239 --> 00:49:47,719 Speaker 1: the opposite of progress. I mean, those were funerals that 800 00:49:48,080 --> 00:49:53,359 Speaker 1: nobody should have had to go to UM So, yes, 801 00:49:53,440 --> 00:49:57,960 Speaker 1: the quote, And honestly, when Emmanuel death happened, that was 802 00:49:58,000 --> 00:50:01,080 Speaker 1: when I took what had been a priv reflection that 803 00:50:01,160 --> 00:50:04,000 Speaker 1: I sent to Janet Yell and in Member Nankee, because 804 00:50:04,000 --> 00:50:06,959 Speaker 1: they were heads of the American Economics Association, to say 805 00:50:07,040 --> 00:50:13,000 Speaker 1: we have a problem. And when Emmanuel killed himself, I said, 806 00:50:13,280 --> 00:50:18,200 Speaker 1: I needed to tell more people because this has to stop. 807 00:50:18,680 --> 00:50:21,600 Speaker 1: So let's get into some specifics. Some of the things 808 00:50:21,600 --> 00:50:26,000 Speaker 1: you mentioned in your boast involved misogyny and sexism and 809 00:50:26,120 --> 00:50:32,000 Speaker 1: racism and other things. Let's let's start with the New 810 00:50:32,080 --> 00:50:36,960 Speaker 1: York Times quote um from June of this year, economics 811 00:50:37,040 --> 00:50:41,000 Speaker 1: dominated by white men is royaled by Black Lives Matter? 812 00:50:41,560 --> 00:50:46,399 Speaker 1: So is economics dominated by men and is a mixed 813 00:50:46,480 --> 00:50:50,279 Speaker 1: mostly white and what should we be doing about that? Yes, 814 00:50:51,080 --> 00:50:56,760 Speaker 1: there's absolutely a domination in the sense that the elite 815 00:50:56,800 --> 00:50:59,759 Speaker 1: members of the profession, the ones you see on t 816 00:51:00,040 --> 00:51:03,799 Speaker 1: be the ones who are in the White House, in 817 00:51:03,840 --> 00:51:08,080 Speaker 1: the top positions, many many of them are white men. 818 00:51:09,200 --> 00:51:12,040 Speaker 1: I like to joke, and I've been to so many seminars, 819 00:51:12,160 --> 00:51:17,920 Speaker 1: especially these online virtual seminars about COVID with macroeconomists, so 820 00:51:17,960 --> 00:51:20,520 Speaker 1: many of them. It is just a sea of whiteness 821 00:51:20,640 --> 00:51:23,200 Speaker 1: and maleness. And I like to joke that the diversity 822 00:51:23,239 --> 00:51:26,000 Speaker 1: here is the degree of hair loss, right, Like, I mean, 823 00:51:26,080 --> 00:51:29,120 Speaker 1: this is and um, you know, I'm kind of a 824 00:51:29,120 --> 00:51:32,280 Speaker 1: paint and in general, but you know this is serious 825 00:51:32,280 --> 00:51:34,799 Speaker 1: that you've gon joke about it. But that means that 826 00:51:34,880 --> 00:51:38,719 Speaker 1: you are not bringing the lived experiences. White men do 827 00:51:38,800 --> 00:51:42,840 Speaker 1: not experience misogyny like I mean, they can experience something 828 00:51:42,840 --> 00:51:45,120 Speaker 1: from women that you know and being degraded by other 829 00:51:45,200 --> 00:51:48,160 Speaker 1: men colleagues. But white men also just like I as 830 00:51:48,200 --> 00:51:52,319 Speaker 1: a white woman, do not experience racism. Like I can 831 00:51:52,360 --> 00:51:56,719 Speaker 1: be empathetic, but I will never walk in those shoes. Right, 832 00:51:56,800 --> 00:52:00,879 Speaker 1: So you can as a researcher, are like I can 833 00:52:00,960 --> 00:52:05,239 Speaker 1: write about race, I can think about race, but particularly 834 00:52:05,320 --> 00:52:09,160 Speaker 1: during Black Lives Matter, I still figured out, you know, 835 00:52:09,520 --> 00:52:12,359 Speaker 1: my voice is not what we hear need to hear 836 00:52:12,480 --> 00:52:17,120 Speaker 1: right now. But I can amplify the voices, particularly of 837 00:52:17,200 --> 00:52:21,200 Speaker 1: black scholars, because I can retweet. You know, I have 838 00:52:21,280 --> 00:52:23,280 Speaker 1: a platform on Twitter that a lot of them don't. 839 00:52:23,640 --> 00:52:26,120 Speaker 1: And to me, I wanted the world and I needed 840 00:52:26,120 --> 00:52:30,640 Speaker 1: to see their voices because there are economous There are 841 00:52:30,800 --> 00:52:34,040 Speaker 1: scholars who think very hard, have thought very hard for 842 00:52:34,280 --> 00:52:39,920 Speaker 1: decades about structural racism and injustice in the U. S. 843 00:52:39,960 --> 00:52:44,720 Speaker 1: Economy and the global economy. They exist, they have been marginalized, 844 00:52:44,920 --> 00:52:48,440 Speaker 1: they are told their research is not economics. They're rejected 845 00:52:48,480 --> 00:52:51,319 Speaker 1: from top journals. I saw someone talking about like they 846 00:52:51,320 --> 00:52:53,799 Speaker 1: put racial injustice in a paper and a referee said 847 00:52:53,800 --> 00:52:56,799 Speaker 1: that's inflammatory, and I'm like, no, that's like the real 848 00:52:56,840 --> 00:52:59,719 Speaker 1: world for these people like you know, So that this 849 00:53:00,040 --> 00:53:04,440 Speaker 1: culture and then in addition, we had white men jumping 850 00:53:04,560 --> 00:53:08,280 Speaker 1: into the conversation of black Lives matter in a very 851 00:53:08,280 --> 00:53:13,520 Speaker 1: problematic and frankly racist way. So let's talk a little 852 00:53:13,560 --> 00:53:17,879 Speaker 1: bit about the research aspect of this. A month after 853 00:53:17,960 --> 00:53:21,040 Speaker 1: that Time's Peace was out, there was a Wall Street 854 00:53:21,120 --> 00:53:26,040 Speaker 1: journal piece vote Economic journals faulted for neglecting studies on 855 00:53:26,239 --> 00:53:30,560 Speaker 1: race and discrimination. That was in July of this year, 856 00:53:30,920 --> 00:53:35,680 Speaker 1: to which you responded, economics has a race problem. So 857 00:53:35,920 --> 00:53:39,359 Speaker 1: how do you recognize the race problem? And what can 858 00:53:39,400 --> 00:53:42,799 Speaker 1: you do to solve the race problem? Because in your 859 00:53:42,800 --> 00:53:46,359 Speaker 1: blog post it's apparent it's not just at the big 860 00:53:46,400 --> 00:53:51,000 Speaker 1: institutions in government or Wall Street or corporate America. It 861 00:53:51,120 --> 00:53:56,560 Speaker 1: starts at at freshman academia and goes the whole whole 862 00:53:56,600 --> 00:53:59,960 Speaker 1: way from when you first decided to become an economist 863 00:54:00,000 --> 00:54:03,560 Speaker 1: and follows your entire career. So what can economics do 864 00:54:03,880 --> 00:54:10,040 Speaker 1: about its race problem? It has to do so much 865 00:54:10,360 --> 00:54:13,600 Speaker 1: like there is no magic wand there is no silver bullet. 866 00:54:14,160 --> 00:54:17,759 Speaker 1: The thing that economics has fallen down on and race 867 00:54:18,280 --> 00:54:22,640 Speaker 1: raises frankly a much more serious conversation that we need 868 00:54:22,680 --> 00:54:26,480 Speaker 1: to have the gender right. I mean, Ray is just deplorable. 869 00:54:26,840 --> 00:54:29,520 Speaker 1: And what surprised me about my blog post on many 870 00:54:29,600 --> 00:54:32,840 Speaker 1: different dimensions is I didn't think it was newsworthy because 871 00:54:32,880 --> 00:54:37,120 Speaker 1: everything I said we already knew. Now, the economics profession 872 00:54:37,400 --> 00:54:43,040 Speaker 1: has this amazing ability to explain away its problems. I've 873 00:54:43,080 --> 00:54:46,879 Speaker 1: done a lot of work speaking on gender and economics. 874 00:54:46,920 --> 00:54:49,000 Speaker 1: I don't do research in this area, but again, I 875 00:54:49,080 --> 00:54:53,040 Speaker 1: want to amplify the research, and I have a presentation 876 00:54:53,080 --> 00:54:56,000 Speaker 1: where I go through and debunk every single one of 877 00:54:56,040 --> 00:54:59,520 Speaker 1: the criticisms. One of them is women can't do maths. 878 00:54:59,560 --> 00:55:02,239 Speaker 1: This is not true. Plenty of women are math majors. 879 00:55:02,280 --> 00:55:05,239 Speaker 1: Another one is well, women just don't want to do economics. 880 00:55:05,360 --> 00:55:07,400 Speaker 1: And it's like, well, why do you think that's the case, 881 00:55:07,840 --> 00:55:10,320 Speaker 1: right Like, if they show up and you say sexually 882 00:55:10,360 --> 00:55:14,279 Speaker 1: explicit jokes in class, they might not feel real comfortable, 883 00:55:14,480 --> 00:55:20,279 Speaker 1: or if the curriculum doesn't even talk about it, right like. 884 00:55:20,360 --> 00:55:22,880 Speaker 1: And so it just shows that a lot of economists 885 00:55:22,920 --> 00:55:29,680 Speaker 1: either are completely ignorant of race, or in some cases, 886 00:55:29,920 --> 00:55:35,040 Speaker 1: they are openly hostile to raise and many of these 887 00:55:35,080 --> 00:55:38,960 Speaker 1: people not everyone. I don't there could people in economics, right, 888 00:55:39,400 --> 00:55:43,640 Speaker 1: but too often, in too many cases, we have gatekeepers 889 00:55:43,680 --> 00:55:49,759 Speaker 1: of the profession who are not being inclusive. They're doing 890 00:55:49,800 --> 00:55:52,759 Speaker 1: the opposite, they're pushing people away. And if that is 891 00:55:52,760 --> 00:55:55,680 Speaker 1: the case, then you have a big problem. And frankly, like, 892 00:55:55,760 --> 00:55:59,520 Speaker 1: how do I know it? Because look around, like there 893 00:55:59,640 --> 00:56:03,800 Speaker 1: was one black woman economists out of over four hundreds 894 00:56:04,080 --> 00:56:07,359 Speaker 1: that I worked with at the Federal Reserves. Over time, 895 00:56:07,440 --> 00:56:09,799 Speaker 1: there's like two other black people that I know that 896 00:56:09,880 --> 00:56:13,759 Speaker 1: have worked and have since left. Like, seriously, don't you 897 00:56:13,960 --> 00:56:17,600 Speaker 1: think maybe you know and so? And you can see 898 00:56:17,640 --> 00:56:20,799 Speaker 1: this in top journals. Good luck, good luck finding a 899 00:56:20,840 --> 00:56:25,759 Speaker 1: black person Latina Asian, Like, there's just there. There's so 900 00:56:25,920 --> 00:56:30,160 Speaker 1: many layers of pushing people away that we need because 901 00:56:30,200 --> 00:56:34,239 Speaker 1: they bring something in an authentic way that most of 902 00:56:34,320 --> 00:56:40,600 Speaker 1: us can't. Huh. Quite interesting, And our last question on 903 00:56:40,800 --> 00:56:45,880 Speaker 1: economics problems, this is a quote from your blog post 904 00:56:46,320 --> 00:56:52,760 Speaker 1: quote economics hurt people outside economics with bad policy advice. Explain. 905 00:56:54,560 --> 00:56:58,239 Speaker 1: So this goes back to my soul searching in the 906 00:56:58,440 --> 00:57:02,080 Speaker 1: very worst time time of the recovery from the Great Recession, 907 00:57:02,280 --> 00:57:05,040 Speaker 1: when I was like, how did we miss this at 908 00:57:05,040 --> 00:57:09,480 Speaker 1: the Federal Reserve the crisis, the housing crisis? How did 909 00:57:09,480 --> 00:57:12,960 Speaker 1: we miss it now in the Great Recession the recovery. 910 00:57:13,239 --> 00:57:17,480 Speaker 1: And I got to this point of saying, it's because 911 00:57:17,560 --> 00:57:21,120 Speaker 1: we do not have diversity. The diversity comes in a 912 00:57:21,200 --> 00:57:26,000 Speaker 1: lot of dimensions. And the thing that really nailed it 913 00:57:26,080 --> 00:57:29,040 Speaker 1: for me is I went back again. I was really 914 00:57:29,080 --> 00:57:31,760 Speaker 1: trying to understand this, Like, I was so puzzled. And 915 00:57:31,840 --> 00:57:34,000 Speaker 1: I'm one of those people that loves to read FED 916 00:57:34,040 --> 00:57:37,560 Speaker 1: transcripts from the Federal Open Market Committee meeting. So I 917 00:57:37,600 --> 00:57:41,760 Speaker 1: started pouring through the transcripts prior to the financial crisis, 918 00:57:42,480 --> 00:57:45,000 Speaker 1: and I found a meeting and I go back in 919 00:57:45,120 --> 00:57:47,640 Speaker 1: my like low points of being at the FED or 920 00:57:47,680 --> 00:57:50,800 Speaker 1: just doing economic policy, and I reread this one transcript. 921 00:57:51,200 --> 00:57:54,880 Speaker 1: It was in two thousand five. Josh Gallen, who has 922 00:57:55,040 --> 00:57:59,800 Speaker 1: now a very senior economist as the board, he was 923 00:57:59,840 --> 00:58:02,840 Speaker 1: a junior economist. Then he briefed off and see he 924 00:58:03,040 --> 00:58:06,240 Speaker 1: argued that house prices were overvalued. This is in two 925 00:58:06,240 --> 00:58:09,840 Speaker 1: thousand five. The whole I mean green space like everybody else. 926 00:58:09,920 --> 00:58:13,000 Speaker 1: There's some exceptions, but basically everyone else at this meeting, 927 00:58:13,720 --> 00:58:17,360 Speaker 1: especially the ones that were very prominent like Greenspan totally 928 00:58:17,400 --> 00:58:21,160 Speaker 1: shut him down. Now years later, I've always told Josh 929 00:58:21,280 --> 00:58:23,560 Speaker 1: I like, he's a hero. He spoke up, like I 930 00:58:23,600 --> 00:58:25,960 Speaker 1: tried to speak up. You get like smothered when you 931 00:58:25,960 --> 00:58:28,200 Speaker 1: try to speak up. But if you're persistent, I'm a 932 00:58:28,240 --> 00:58:31,960 Speaker 1: persistent person, you can move. The needle is a very 933 00:58:32,000 --> 00:58:35,400 Speaker 1: slow moving needle, but it does move. And recently I 934 00:58:35,440 --> 00:58:38,040 Speaker 1: saw him and he knows, like, I sah, you're my hero, 935 00:58:38,400 --> 00:58:42,360 Speaker 1: and he's like, but Claudia, I never forgave myself because 936 00:58:42,360 --> 00:58:45,200 Speaker 1: he said after they came down, after they explained it away, 937 00:58:45,560 --> 00:58:51,080 Speaker 1: I could have kept pushing loudly and I didn't, And 938 00:58:51,120 --> 00:58:54,080 Speaker 1: I thought, to me, that was a really important lesson. 939 00:58:54,240 --> 00:58:58,880 Speaker 1: And I have been not with the consensus since this 940 00:58:59,000 --> 00:59:03,280 Speaker 1: crisis started. I have very loudly said we have the 941 00:59:03,520 --> 00:59:06,880 Speaker 1: mother of all demand shocks, like, yes, the pandemic is, 942 00:59:07,040 --> 00:59:09,280 Speaker 1: you know, causing what we you know, a supply shock, 943 00:59:09,760 --> 00:59:12,040 Speaker 1: but this is a big one. And I spent a 944 00:59:12,080 --> 00:59:14,120 Speaker 1: lot of time and I was told by people who 945 00:59:14,160 --> 00:59:18,120 Speaker 1: I have very much respect in economic policy circle, its Claudie, 946 00:59:18,160 --> 00:59:20,240 Speaker 1: you need to tone it down because you're gonna look 947 00:59:20,240 --> 00:59:22,720 Speaker 1: bad at the other side of this. And I was like, 948 00:59:22,840 --> 00:59:26,080 Speaker 1: I won't right, and I didn't back down on the 949 00:59:26,120 --> 00:59:30,200 Speaker 1: blog post because I know people that have hurt and 950 00:59:30,280 --> 00:59:33,640 Speaker 1: are continued to be hurt. Like I'm fine nine years 951 00:59:33,640 --> 00:59:36,360 Speaker 1: ago when they come in my office, I'm like, yeah, 952 00:59:36,440 --> 00:59:39,880 Speaker 1: go away. Uh, but I know people that have been 953 00:59:39,960 --> 00:59:44,240 Speaker 1: hurt are being hurt, not just the FED but all 954 00:59:44,280 --> 00:59:47,360 Speaker 1: over and the undergrads that I hear from where the 955 00:59:47,400 --> 00:59:49,800 Speaker 1: people have been pushed out of the profession. I mean, 956 00:59:49,840 --> 00:59:52,760 Speaker 1: they make me angry. He read the post. I found angry. 957 00:59:53,200 --> 00:59:57,280 Speaker 1: I am like, this is completely unfair. And so many 958 00:59:57,320 --> 01:00:00,720 Speaker 1: of them would have been great economists. I know it, 959 01:00:01,000 --> 01:00:03,280 Speaker 1: some of them. I saw their research getting going. I 960 01:00:03,320 --> 01:00:05,919 Speaker 1: was so excited, and they walked away and I said, 961 01:00:05,960 --> 01:00:08,800 Speaker 1: you know what, we don't deserve you. We need you, 962 01:00:08,880 --> 01:00:11,280 Speaker 1: but we don't deserve you. And like that has to change, 963 01:00:11,320 --> 01:00:14,720 Speaker 1: because until it changes, we are going to continue to 964 01:00:14,800 --> 01:00:19,400 Speaker 1: give advice that is not aware of. Well, how do 965 01:00:19,480 --> 01:00:23,000 Speaker 1: people of color, how does it less educated, How do 966 01:00:23,080 --> 01:00:26,360 Speaker 1: the people on the margins of the economy experience a recession? 967 01:00:27,000 --> 01:00:30,120 Speaker 1: Let's talk about that. Let's do research on that. And 968 01:00:30,280 --> 01:00:33,280 Speaker 1: it has been ignored, and the Federal Reserve has done 969 01:00:33,360 --> 01:00:37,520 Speaker 1: so much to improve that research. But like where was 970 01:00:37,560 --> 01:00:41,800 Speaker 1: it in two thousand eight? Like how is it possible? 971 01:00:42,200 --> 01:00:44,520 Speaker 1: Because it was out in the world, out in academia, 972 01:00:44,560 --> 01:00:47,920 Speaker 1: out in other policy circles. This conversation was happening, this 973 01:00:48,120 --> 01:00:53,280 Speaker 1: research was happening, and we just totally ignored it. Wow, 974 01:00:53,520 --> 01:00:57,440 Speaker 1: quite fascinating. I am almost out of time. I know 975 01:00:57,520 --> 01:01:00,440 Speaker 1: we only have you for an hour, So let jumped 976 01:01:00,520 --> 01:01:04,560 Speaker 1: to our speed round. These are our favorite questions we 977 01:01:04,600 --> 01:01:07,960 Speaker 1: ask all our guests. There sixty seconds each and it's 978 01:01:07,960 --> 01:01:10,000 Speaker 1: how we wrap up the show each week. So let's 979 01:01:10,080 --> 01:01:13,200 Speaker 1: jump right into this. Tell us what you're streaming these days. 980 01:01:13,240 --> 01:01:16,160 Speaker 1: Give us your favorite either Netflix or Amazon shows, or 981 01:01:16,200 --> 01:01:21,240 Speaker 1: any podcasts you're listening to. So I have become an 982 01:01:21,280 --> 01:01:25,000 Speaker 1: avid podcast listener, right. I didn't think I would because 983 01:01:25,040 --> 01:01:26,920 Speaker 1: for a long time I like to read. I loved 984 01:01:26,920 --> 01:01:29,960 Speaker 1: econ blogs, but they just they aren't what they used 985 01:01:30,000 --> 01:01:33,280 Speaker 1: to be, uh in terms of just not as many voices. 986 01:01:33,320 --> 01:01:35,480 Speaker 1: So I was like, Okay, I'm gonna I'm gonna listen 987 01:01:35,480 --> 01:01:38,320 Speaker 1: to these podcasts. One of my coping mechanisms in this 988 01:01:38,440 --> 01:01:42,040 Speaker 1: crisis has been go fred long walk every day, and 989 01:01:42,120 --> 01:01:45,800 Speaker 1: podcasts made a great soundtrack to my long walk. I 990 01:01:45,960 --> 01:01:50,480 Speaker 1: listened to a very wide range of podcast I listened 991 01:01:51,040 --> 01:01:57,000 Speaker 1: to The Indicator, I listened to various podcasts on Bloomer. 992 01:01:57,160 --> 01:02:01,320 Speaker 1: I love Joe Wisenal and Tracy ol Ways podcast. I 993 01:02:01,440 --> 01:02:06,240 Speaker 1: just it's so informative and they're fun, right. And I 994 01:02:06,320 --> 01:02:10,840 Speaker 1: listen to the Brunix, right, Matt and Elizabeth Brune. I mean, 995 01:02:10,840 --> 01:02:13,560 Speaker 1: this is a very different perspective. I don't always agree 996 01:02:13,560 --> 01:02:16,720 Speaker 1: with them, it's very interesting. And I listen to podcasts 997 01:02:16,720 --> 01:02:21,560 Speaker 1: that are not about economics. A friend pointed me Caatebon 998 01:02:21,720 --> 01:02:25,520 Speaker 1: pointed me to Forever thirty five. It's about facial products 999 01:02:25,600 --> 01:02:27,760 Speaker 1: and like what to wear in the pandemic from these 1000 01:02:27,760 --> 01:02:30,120 Speaker 1: two women, and it's like, I need to take a 1001 01:02:30,200 --> 01:02:33,880 Speaker 1: break from economics sometimes, right. And so to me, it's 1002 01:02:33,920 --> 01:02:38,160 Speaker 1: been a great way just to hear people other voices. 1003 01:02:38,280 --> 01:02:41,280 Speaker 1: And I've been really privileged, like today to actually be 1004 01:02:41,400 --> 01:02:44,240 Speaker 1: part of those conversations. I can never listen to the 1005 01:02:44,280 --> 01:02:46,920 Speaker 1: ones that I'm on later, um, but I love the 1006 01:02:46,960 --> 01:02:49,800 Speaker 1: fact it's a it's a it's a difficult skill to 1007 01:02:49,960 --> 01:02:53,560 Speaker 1: learn to listen to yourself without cringing. Trust me, I 1008 01:02:53,680 --> 01:02:56,880 Speaker 1: know from where I come. Second question, who are your 1009 01:02:56,920 --> 01:03:01,720 Speaker 1: mentors who helped shape your career, so I have a 1010 01:03:01,760 --> 01:03:05,440 Speaker 1: lot of them. Sarabe Dad was my first economics professor 1011 01:03:05,480 --> 01:03:09,080 Speaker 1: at Dennison. He was my senior thesis advisor. I wouldn't 1012 01:03:09,080 --> 01:03:12,120 Speaker 1: be an economist if he hadn't like really pushed me. 1013 01:03:12,120 --> 01:03:14,760 Speaker 1: And I learned economic history from him, like I never 1014 01:03:14,760 --> 01:03:17,760 Speaker 1: saw that again, history of economic thought at the University 1015 01:03:17,800 --> 01:03:21,520 Speaker 1: of Michigan. Matthew Shapiro was my advisor. I continue to 1016 01:03:21,600 --> 01:03:25,040 Speaker 1: come to him and especially recently with advice. I do 1017 01:03:25,160 --> 01:03:29,040 Speaker 1: research with him. He's just really important and you have 1018 01:03:29,120 --> 01:03:32,320 Speaker 1: to have allies, and I need an ally that understood economics. 1019 01:03:32,360 --> 01:03:35,000 Speaker 1: But my parents are awesome, but they're like, listen to Matthew. 1020 01:03:35,120 --> 01:03:37,080 Speaker 1: He cares and he understands your world. We do not 1021 01:03:37,160 --> 01:03:41,280 Speaker 1: understand your world. And I will say a big mentor 1022 01:03:42,120 --> 01:03:45,840 Speaker 1: an ally to me. David Lebo was my first section 1023 01:03:45,920 --> 01:03:49,040 Speaker 1: chief at the Board, and he is someone who I 1024 01:03:49,080 --> 01:03:52,080 Speaker 1: always felt I could go to. He was someone I 1025 01:03:52,120 --> 01:03:55,120 Speaker 1: went to when I just completely melted down in two 1026 01:03:55,200 --> 01:03:59,959 Speaker 1: thousand eleven, and it's really special to have people who 1027 01:04:00,040 --> 01:04:02,720 Speaker 1: you know you can go to. They care about you 1028 01:04:02,800 --> 01:04:05,040 Speaker 1: and they will not judge you. Because I was a 1029 01:04:05,080 --> 01:04:08,760 Speaker 1: total mess and he helped me get better. He gave 1030 01:04:08,760 --> 01:04:10,960 Speaker 1: me the space, he made sure they didn't fire me. 1031 01:04:11,480 --> 01:04:14,880 Speaker 1: Um and and I try to do that as a mentor. 1032 01:04:15,600 --> 01:04:17,600 Speaker 1: The thing that I learned and I pushed out this 1033 01:04:17,640 --> 01:04:20,120 Speaker 1: post is I learned that like helping people get better 1034 01:04:20,200 --> 01:04:23,320 Speaker 1: and as the absolute first thing to do is important, 1035 01:04:23,720 --> 01:04:26,080 Speaker 1: but if you don't go back and try and figure 1036 01:04:26,120 --> 01:04:29,880 Speaker 1: out how to shut down the harasser, it doesn't stop. 1037 01:04:29,960 --> 01:04:32,200 Speaker 1: And that's a very recent lesson for me. And that's 1038 01:04:32,240 --> 01:04:35,680 Speaker 1: a tough lesson for all of the allies I've had 1039 01:04:35,760 --> 01:04:39,080 Speaker 1: because they just want to help me and I get 1040 01:04:39,200 --> 01:04:41,520 Speaker 1: and that's what I needed most. But I also there's 1041 01:04:41,520 --> 01:04:43,560 Speaker 1: a systemic problem. We've got to fix it, and it 1042 01:04:43,560 --> 01:04:46,320 Speaker 1: will be the allies that do it, but we we 1043 01:04:46,440 --> 01:04:50,880 Speaker 1: gotta we gotta do it, alright. So our favorite question, 1044 01:04:50,960 --> 01:04:53,680 Speaker 1: this is the one that everybody always asks about. Tell 1045 01:04:53,760 --> 01:04:56,200 Speaker 1: us what you're reading? What are you reading currently? And 1046 01:04:56,240 --> 01:04:59,880 Speaker 1: one are some of your all time favorite books? The 1047 01:05:00,000 --> 01:05:03,560 Speaker 1: this one is tough. Like I read a lot and frankly, 1048 01:05:04,600 --> 01:05:08,080 Speaker 1: I read a lot of Twitter, right like I just um, 1049 01:05:08,120 --> 01:05:11,640 Speaker 1: I am what Tyler Cowen refers to as an info war, 1050 01:05:12,480 --> 01:05:15,840 Speaker 1: Like I just love all this stuff flying by me, 1051 01:05:16,680 --> 01:05:20,920 Speaker 1: and that unfortunately means that, like, that's what I spend 1052 01:05:20,960 --> 01:05:23,080 Speaker 1: a lot of time doing, right, because I can't read 1053 01:05:23,080 --> 01:05:28,000 Speaker 1: two things at once. Um, and I'm going to send 1054 01:05:28,000 --> 01:05:32,760 Speaker 1: you a tweet showing you one book. I'm going to 1055 01:05:32,880 --> 01:05:35,400 Speaker 1: send you a tweet showing you my biggest fear during 1056 01:05:35,440 --> 01:05:40,919 Speaker 1: the pandemic is not reading any books and only reading Twitter. Yeah, 1057 01:05:40,960 --> 01:05:43,439 Speaker 1: and I read a lot of journal articles. I mean, 1058 01:05:43,440 --> 01:05:48,560 Speaker 1: economics does not have a culture of writing books. Though 1059 01:05:48,560 --> 01:05:50,760 Speaker 1: our paper drew up in eighty pages, so it's kind 1060 01:05:50,760 --> 01:05:53,880 Speaker 1: of like a little mini book. What sort of advice 1061 01:05:53,880 --> 01:05:57,800 Speaker 1: would you give to a recent college graduate just beginning 1062 01:05:58,000 --> 01:06:04,240 Speaker 1: their career in economics? It's not your fault as a 1063 01:06:04,320 --> 01:06:08,120 Speaker 1: new person. No, I'm serious and actually right now and 1064 01:06:08,680 --> 01:06:11,800 Speaker 1: imports like putting it in the context of this recession. 1065 01:06:12,560 --> 01:06:14,920 Speaker 1: People who are early in their career, people who are 1066 01:06:14,960 --> 01:06:18,600 Speaker 1: graduating college, people who are finishing up their PhDs this year, 1067 01:06:19,240 --> 01:06:22,720 Speaker 1: they are going to have a very rough time. And 1068 01:06:22,760 --> 01:06:25,120 Speaker 1: there's research that shows that you have a rough time 1069 01:06:25,160 --> 01:06:29,240 Speaker 1: for a whole career. Like these poor millennials. We totally 1070 01:06:29,240 --> 01:06:31,280 Speaker 1: slammed them because it came out in the job market 1071 01:06:31,440 --> 01:06:33,640 Speaker 1: in the early days of the Great Recession and its 1072 01:06:33,680 --> 01:06:36,360 Speaker 1: recovery and oh my gosh, they finally have enough money 1073 01:06:36,360 --> 01:06:39,240 Speaker 1: to buy a house, and we're doing this to them again, right, 1074 01:06:39,360 --> 01:06:42,240 Speaker 1: So I just it's important in like the context of 1075 01:06:42,280 --> 01:06:45,520 Speaker 1: the world that you're in, like it's not their fault. 1076 01:06:46,040 --> 01:06:48,880 Speaker 1: Matthew Shapiro reminds me that the macro economy is not 1077 01:06:48,920 --> 01:06:51,600 Speaker 1: my fault because you know, it's a good forecaster. I 1078 01:06:51,640 --> 01:06:53,600 Speaker 1: can't fix this, and so I have to like chill 1079 01:06:53,600 --> 01:06:58,080 Speaker 1: out a little bit um And but in terms of 1080 01:06:58,160 --> 01:07:00,560 Speaker 1: and it's not your fault is also porton. When you 1081 01:07:00,600 --> 01:07:04,000 Speaker 1: get into a this profession of economics, you're going to 1082 01:07:04,160 --> 01:07:07,480 Speaker 1: see things differently than the more senior people. Like we 1083 01:07:07,600 --> 01:07:10,080 Speaker 1: forget what it's like to be new. We forget like 1084 01:07:10,160 --> 01:07:13,440 Speaker 1: how problematic some of our norms are. So you have 1085 01:07:13,600 --> 01:07:17,760 Speaker 1: your eyes open and it's really hard to balance this. 1086 01:07:17,760 --> 01:07:20,120 Speaker 1: This doesn't feel okay, but I feel like I gotta 1087 01:07:20,200 --> 01:07:23,600 Speaker 1: do it to fit in. And and when something bad 1088 01:07:23,680 --> 01:07:26,600 Speaker 1: happens too often, I see young economists and I did 1089 01:07:26,640 --> 01:07:31,440 Speaker 1: this to blaming themselves and it's not about them. It's 1090 01:07:31,480 --> 01:07:33,760 Speaker 1: it's a it's not about the person who has heard, 1091 01:07:33,800 --> 01:07:36,600 Speaker 1: it's about the person who's hurting them. But like that's 1092 01:07:36,600 --> 01:07:39,600 Speaker 1: a tricky thing. And that's like, you know, pro pro 1093 01:07:39,960 --> 01:07:43,400 Speaker 1: tip of like working through a career. Right, this is 1094 01:07:43,400 --> 01:07:47,520 Speaker 1: not just economics, but if you haven't lived it, how 1095 01:07:47,640 --> 01:07:51,640 Speaker 1: how would you possibly know how to react to it? Huh? 1096 01:07:51,920 --> 01:07:55,880 Speaker 1: Quite quite interesting. And our final speed round question, what 1097 01:07:55,920 --> 01:07:58,640 Speaker 1: do you know about the world of economics today that 1098 01:07:58,680 --> 01:08:01,800 Speaker 1: you wish you knew twenty years ago? Were so when 1099 01:08:01,800 --> 01:08:07,600 Speaker 1: you were first getting out of school. I became an 1100 01:08:07,600 --> 01:08:11,240 Speaker 1: economist because I believe that economics could do good in 1101 01:08:11,280 --> 01:08:15,760 Speaker 1: the world, and in particular, I became a macro economist 1102 01:08:15,880 --> 01:08:20,479 Speaker 1: because I believed economic policy, like the big stuff, could 1103 01:08:20,479 --> 01:08:24,120 Speaker 1: do good. Again, it was there to do good. And 1104 01:08:24,760 --> 01:08:27,920 Speaker 1: something I have grappled with in my career as an 1105 01:08:27,920 --> 01:08:34,320 Speaker 1: economic policy advisor is we don't always do good. Now 1106 01:08:34,360 --> 01:08:37,439 Speaker 1: I am, I am totally a glass half full, if 1107 01:08:37,439 --> 01:08:40,040 Speaker 1: not overflowing. I have a lot of energy. I did 1108 01:08:40,120 --> 01:08:43,519 Speaker 1: not give up, and I think we can do this 1109 01:08:43,600 --> 01:08:47,680 Speaker 1: and we definitely do in some cases. But as like economics, 1110 01:08:47,880 --> 01:08:50,200 Speaker 1: we got to do more good in the world. And 1111 01:08:50,240 --> 01:08:52,400 Speaker 1: I think for me that was you know, I'm a 1112 01:08:52,520 --> 01:08:55,280 Speaker 1: naive person and I love people and I think everyone 1113 01:08:55,280 --> 01:08:58,559 Speaker 1: else should. But you know, like there are racist and 1114 01:08:58,600 --> 01:09:02,000 Speaker 1: misogynists and people were totally close minded and we'll protect 1115 01:09:02,040 --> 01:09:05,080 Speaker 1: their elite position, and it's like, yeah, we've got to 1116 01:09:05,160 --> 01:09:07,320 Speaker 1: change that, because like that is not helping us do 1117 01:09:07,400 --> 01:09:11,120 Speaker 1: good in the world. Thanks so much, Claudia for being 1118 01:09:11,160 --> 01:09:13,960 Speaker 1: so generous with your time. We have been speaking with 1119 01:09:14,000 --> 01:09:17,680 Speaker 1: Claudia sam She is a former senior economist in the 1120 01:09:17,760 --> 01:09:21,320 Speaker 1: Council of Economic Advisors for the Obama administration, as well 1121 01:09:21,360 --> 01:09:25,160 Speaker 1: as being a researcher and section chief for the Board 1122 01:09:25,160 --> 01:09:29,439 Speaker 1: of Governors for the Federal Reserve. If you enjoy this conversation, well, 1123 01:09:29,560 --> 01:09:31,320 Speaker 1: be sure to look up an Incher Down an Inch 1124 01:09:31,360 --> 01:09:33,960 Speaker 1: on Apple iTunes and you can see any of the 1125 01:09:34,000 --> 01:09:38,000 Speaker 1: previous three hundred plus conversations we've done over the past 1126 01:09:38,320 --> 01:09:41,759 Speaker 1: Wow six years. That's a long time. You can also 1127 01:09:41,840 --> 01:09:47,519 Speaker 1: find us at any of your favorite podcast hosts, Spotify, Overcast, Stitcher, 1128 01:09:47,760 --> 01:09:51,040 Speaker 1: wherever finer podcasts are sold. You can check out my 1129 01:09:51,120 --> 01:09:55,479 Speaker 1: weekly column on Bloomberg dot com Slash Opinion, follow me 1130 01:09:55,520 --> 01:09:58,759 Speaker 1: on Twitter at rit Halts, sign up for our daily 1131 01:09:58,840 --> 01:10:02,000 Speaker 1: reads at rit Halts dot com. I would be remiss 1132 01:10:02,080 --> 01:10:04,360 Speaker 1: if I did not thank the crack staff that helps 1133 01:10:04,400 --> 01:10:09,400 Speaker 1: put this conversation together each week. Michael Boyle is my producer. 1134 01:10:09,720 --> 01:10:13,519 Speaker 1: Maroufal is our audio engineer. Michael bat Nick is my 1135 01:10:13,560 --> 01:10:16,879 Speaker 1: head of research. Attica val Brunn is our project manager. 1136 01:10:17,400 --> 01:10:20,919 Speaker 1: I'm Barry Ritolts. You've been listening to Masters in Business 1137 01:10:21,320 --> 01:10:22,479 Speaker 1: on Bloomberg Radio.