WEBVTT - Constance Hunter Discusses International Finance 0:00:02.320 --> 0:00:06.880 This is Masters in Business with Barry Ridholts on Bloomberg Radio. 0:00:09.280 --> 0:00:12.000 This week on the podcast, I have a special guest. 0:00:12.080 --> 0:00:16.959 Her name is Constance Hunter. She is the chief economist 0:00:17.079 --> 0:00:23.160 at accounting and consulting giant KPMG. She's also a fishing buddy. 0:00:23.200 --> 0:00:25.800 I've spent some time with her up in Maine at 0:00:25.880 --> 0:00:30.360 Camp Ko Talk discussing all manner of things. She has 0:00:30.400 --> 0:00:36.080 a really interesting and fascinating career path not the typical economists. 0:00:36.120 --> 0:00:39.239 She started on the bye side as a trader and 0:00:39.360 --> 0:00:44.320 fund manager. Eventually UH did some work managing alternative investments 0:00:44.640 --> 0:00:49.199 before she ended up as chief economist at KPMG. This 0:00:49.280 --> 0:00:52.720 is a really interesting conversation I expect you will find 0:00:52.720 --> 0:00:57.760 in intriguing with no further ado, my conversation with Constance Hunter. 0:01:02.000 --> 0:01:05.880 My guest today is Constance Hunter. She has been chief 0:01:05.880 --> 0:01:12.120 economist at KPMG since previously, she was the Deputy Chief 0:01:12.120 --> 0:01:17.320 Investment Officer for fixed income at ACTA Investment Managers, where 0:01:17.360 --> 0:01:21.400 she joined after fifteen years on the by side, investing 0:01:21.440 --> 0:01:26.399 globally in fixed income equities and foreign exchange. She is 0:01:26.440 --> 0:01:30.679 a member of the New York Association of Business Economics 0:01:30.720 --> 0:01:34.880 and one hundred Women in Finance. She also participates in 0:01:34.920 --> 0:01:39.600 the National Committee for US China Relations, working on track 0:01:39.680 --> 0:01:44.959 to economic dialogues. She earned her master's degree in International 0:01:44.959 --> 0:01:49.280 Affairs at Columbia. Constance Hunter, Welcome to Bloomberg. Berry is 0:01:49.360 --> 0:01:51.680 so good to be here. So Constance, let's talk a 0:01:51.720 --> 0:01:54.320 little bit about your background. How did you find your 0:01:54.320 --> 0:01:59.720 way into finance? So a couple of ways. First, my father, 0:02:00.480 --> 0:02:04.080 uh worked for an investment bank in Philadelphia, and so 0:02:04.120 --> 0:02:07.040 there was investing going on in my family. That's where 0:02:07.040 --> 0:02:09.400 you grew up. I grew up in Philadelphia. And and 0:02:09.400 --> 0:02:13.079 then how did you manage to make your way to Manhattan? Well, 0:02:13.080 --> 0:02:15.959 I went to ny U. But the other influence that 0:02:16.000 --> 0:02:20.480 got me into finance my very good friend father, Dan Bongovanni, 0:02:20.639 --> 0:02:24.800 was an avid reader, and so he was reading a 0:02:24.840 --> 0:02:29.360 book called The Coming Economic War with Japan, and I was, 0:02:29.960 --> 0:02:31.840 I know, this was the early eighties. I was in 0:02:31.919 --> 0:02:34.840 high school. And let me just let me just set 0:02:34.840 --> 0:02:39.079 the scene a little bit. The Japanese are dominating exports, 0:02:39.160 --> 0:02:42.560 They're buying Rockefell Or Center. They're gonna take over America, 0:02:42.600 --> 0:02:45.080 take over America a little bit like China today. But 0:02:45.120 --> 0:02:48.919 we'll get back to that Uh. So, I remember he's 0:02:48.960 --> 0:02:51.160 reading this book the Coming Economic War with Japan, and 0:02:51.200 --> 0:02:54.400 the whole concept of an economic war seemed fascinating to me. 0:02:54.440 --> 0:02:57.720 And I was fourteen or fifteen, and so he ended 0:02:57.760 --> 0:02:59.880 up telling me about the book and I borrowed it. 0:03:00.040 --> 0:03:01.600 I read it. I don't you know how much of 0:03:01.639 --> 0:03:03.959 it went over my head, but it I was hooked. 0:03:04.200 --> 0:03:06.880 I was hooked that I not only on finance, but 0:03:07.000 --> 0:03:10.120 on international finance. You end up at n y U. 0:03:10.360 --> 0:03:13.200 Was there a business or international relations in the undergraduate? 0:03:13.320 --> 0:03:16.239 So I did um Liberal Arts, So I have a 0:03:16.320 --> 0:03:19.560 b a. In economics. Uh, And I felt that was important. 0:03:19.639 --> 0:03:24.400 I wanted to have that broad philosophical grounding that a 0:03:24.440 --> 0:03:27.440 good liberal arts degree gives you, um in being able 0:03:27.440 --> 0:03:31.560 to think and baby being able to understand, uh, sort 0:03:31.600 --> 0:03:35.880 of history of Western thought, reading all of the great books. 0:03:35.960 --> 0:03:38.400 That's I think a good grounding for someone who's going 0:03:38.440 --> 0:03:42.760 to spend their career thinking and so. Um. So that 0:03:42.840 --> 0:03:46.120 was my My undergraduate degree was in economics. And then 0:03:46.120 --> 0:03:49.760 you go to Columbia for a master's in International Relationship 0:03:49.920 --> 0:03:53.960 Master so it's a school of International and Public Affairs. 0:03:54.080 --> 0:03:56.480 So my degree is a Master of International affairs, but 0:03:56.520 --> 0:04:00.440 I focused on economics and international economics, and so I 0:04:00.440 --> 0:04:04.680 had professors like jug desbug Waddy and Armenio Fraga, who 0:04:04.800 --> 0:04:07.960 was a adjunct professor when he was at Soros and 0:04:08.000 --> 0:04:10.640 then later went on to become the head of the 0:04:10.640 --> 0:04:15.800 Central Bank of Brazil, for example. So world famous UM faculty. Yes, 0:04:15.880 --> 0:04:19.479 just to say the very least. So you you come 0:04:19.480 --> 0:04:24.000 out with this international relations graduate degree, how does that 0:04:24.040 --> 0:04:28.080 translate to a career on Wall Street? So interestingly enough, 0:04:28.120 --> 0:04:32.000 I was interviewing at Chase Manhattan Bank, so pre Chemical 0:04:32.000 --> 0:04:38.960 Bank merger. I mean, so you're talking n early late 0:04:39.040 --> 0:04:43.000 ninety three, early Ninet'm interviewing at Chase, and they were 0:04:43.040 --> 0:04:46.400 recruiting for the private bank, and I wasn't terribly interested 0:04:46.440 --> 0:04:48.960 in that. UM. I was also interviewing at a bankers 0:04:49.000 --> 0:04:52.200 Trust if anybody go back in time and remember bankers 0:04:52.240 --> 0:04:56.039 Trust for auto analyst position, so very heavily on economics. 0:04:56.080 --> 0:04:59.760 International affairs is important. There's obviously trade component to that. 0:05:00.279 --> 0:05:03.000 So I'm they're interviewing at the private bank, and I 0:05:03.080 --> 0:05:06.600 see this research piece and it's a daily foreign exchange 0:05:06.960 --> 0:05:10.080 update on what happened overnight and what's going on with 0:05:10.120 --> 0:05:13.479 the currencies, and like it was one sentence, maybe two 0:05:13.480 --> 0:05:15.680 sentences about every single economy and a font that I 0:05:15.680 --> 0:05:19.080 couldn't read today to save my life. And and I 0:05:19.120 --> 0:05:21.400 saw this, and I thought, this is what I want 0:05:21.440 --> 0:05:24.080 to do. I want to do this, And so I 0:05:24.160 --> 0:05:27.800 networked my way to the to the Foreign Exchange Department 0:05:27.800 --> 0:05:30.080 and the person who was responsible for this, and it 0:05:30.120 --> 0:05:33.279 turns out they were hiring and and so that person's 0:05:33.360 --> 0:05:35.359 name is chriss Igo, who was also I worked with 0:05:35.400 --> 0:05:39.080 him at ACCA later in my career, and um, he 0:05:39.120 --> 0:05:43.159 had interviewed PhD economists who would say, well, there's a 0:05:43.160 --> 0:05:46.640 perfect information and there's no foreign exchange markets, or you 0:05:46.680 --> 0:05:49.320 know that you can't make any extra money, why forecast them? 0:05:49.800 --> 0:05:52.360 It's all the information is already in the price. And 0:05:52.440 --> 0:05:55.720 here I was coming in looking at the economics and 0:05:55.760 --> 0:05:59.080 the politics and and how they all interplayed with one 0:05:59.080 --> 0:06:01.960 another packed the foreign exchange market. So it was really 0:06:02.000 --> 0:06:04.159 the perfect first job out of graduate school for me. 0:06:04.440 --> 0:06:06.239 And it's funny that two of us are both sitting 0:06:06.240 --> 0:06:09.200 here holding reading glasses in our hands, and you're talking 0:06:09.279 --> 0:06:12.920 about funds. Let me mix this up a little bit 0:06:12.960 --> 0:06:16.760 with you. McKenzie just came out with a study that 0:06:16.920 --> 0:06:21.440 said by the year almost a million jobs will have 0:06:21.560 --> 0:06:26.320 been replaced by and with technology. What does that tell 0:06:26.360 --> 0:06:30.039 you about what's going on in the labor market these days? Okay, 0:06:30.080 --> 0:06:33.800 so let's put this in a big context. The US 0:06:33.920 --> 0:06:37.599 labor market is how many people, hundred and fifty million 0:06:37.600 --> 0:06:42.839 people and fifty exactly, So this is percentagewise, a small 0:06:42.920 --> 0:06:46.159 percentage of total jobs. It sounds big, right, it's a 0:06:46.160 --> 0:06:49.719 little Austin powers. One million jobs are going to disappear, right, 0:06:50.000 --> 0:06:52.080 But but the reality is, first of all, let's so 0:06:52.200 --> 0:06:54.960 contextualize it in terms of the whole labor market. There's 0:06:55.000 --> 0:06:57.839 two other things that need to be highlighted when thinking 0:06:57.839 --> 0:07:00.280 about this issue, and we're actually working on some search 0:07:00.320 --> 0:07:02.560 on this, which I can tell you about in more detail. 0:07:03.560 --> 0:07:05.920 But the first thing is they don't talk about what 0:07:06.000 --> 0:07:09.200 new jobs are going to be created, and that's a 0:07:09.240 --> 0:07:12.160 really important thing to think about. They also don't talk 0:07:12.200 --> 0:07:16.880 about the areas where labor shortages and pending labor shortages 0:07:17.280 --> 0:07:20.720 intersect with the technology. So let me give you one example. 0:07:20.720 --> 0:07:24.280 As the trucking industry and long haul trucking, it's widely 0:07:24.320 --> 0:07:27.840 anticipated we're going to have self driving trucks. And while 0:07:27.880 --> 0:07:30.040 they aren't necessarily we're not necessarily going to have the 0:07:30.120 --> 0:07:33.040 robotics to do the loading of the truck, the unloading 0:07:33.040 --> 0:07:35.000 of the truck, the bringing of the goods into the 0:07:35.080 --> 0:07:39.000 home or the store. Eventually, who knows. We're making progress 0:07:39.040 --> 0:07:42.560 in robotics, but just the driving part is certainly something 0:07:42.880 --> 0:07:44.560 the and the long haul driving part is something that 0:07:44.560 --> 0:07:46.960 could be automated. Young people don't want to do this job. 0:07:47.040 --> 0:07:50.880 It's a very old industry and and you know, you 0:07:50.920 --> 0:07:54.440 can't be on your little dopamine giving device all day 0:07:54.480 --> 0:07:57.000 when that is your job when you're driving a truck. 0:07:57.320 --> 0:07:59.680 And so if we had a self driving truck, that 0:07:59.680 --> 0:08:03.480 could really help an industry that has had to continue 0:08:03.520 --> 0:08:06.840 to raise wages to get people to even consider working 0:08:06.840 --> 0:08:09.320 in that field. It's not something people want to do anymore. 0:08:09.600 --> 0:08:12.000 And that we're talking about right there. It's a it's 0:08:12.000 --> 0:08:14.400 a profession that has two and a half million people. 0:08:14.720 --> 0:08:17.040 So there's there's a match that that's happening in some 0:08:17.120 --> 0:08:20.160 cases where the disappearing of these jobs is a good thing. 0:08:20.520 --> 0:08:23.240 The second thing that they don't talk about, um is 0:08:23.280 --> 0:08:27.000 the number of new jobs that could appear. So someone's 0:08:27.040 --> 0:08:29.600 got a design and build all those robotics. Well, and 0:08:29.680 --> 0:08:33.240 interestingly enough, right now there are more people being employed 0:08:33.800 --> 0:08:39.160 in in artificial intelligence and um robotics than than people 0:08:39.200 --> 0:08:41.240 that are being than jobs that are being destroyed. Now, 0:08:41.240 --> 0:08:42.760 I'm not saying that's going to go on forever, but 0:08:42.800 --> 0:08:46.000 if we look back historically too, when we had guilt, 0:08:46.200 --> 0:08:51.480 when artisans produced things where it took one guy a 0:08:51.600 --> 0:08:54.800 month to produce let's say an ax, right, and he 0:08:54.840 --> 0:08:57.880 produced all parts of that acts. Then we moved away 0:08:57.880 --> 0:08:59.880 from artisans and we had factories and you had one 0:09:00.120 --> 0:09:03.800 producing the handle and one guy producing the top part 0:09:03.800 --> 0:09:06.520 of the metal part of the acts. And then you 0:09:06.600 --> 0:09:09.000 had then you had multiple people working in this factory 0:09:09.040 --> 0:09:13.400 and you could produce. You could have fifteen people producing 0:09:13.480 --> 0:09:17.240 a hundred axes in a month. Right. That's a representative example. 0:09:17.280 --> 0:09:19.760 Those aren't the exact numbers, but the point being that 0:09:20.280 --> 0:09:23.720 you create actually created more jobs because the thing that 0:09:23.760 --> 0:09:27.240 you're producing became less expensive. But you created new types 0:09:27.240 --> 0:09:30.839 of jobs. So the idea of a clerical worker that 0:09:30.880 --> 0:09:35.480 didn't exist, right, You that that role of clerical worker. 0:09:35.520 --> 0:09:38.359 People to do the accounting, people to do hr management, 0:09:38.520 --> 0:09:40.959 people to do building management, all that kind of stuff 0:09:41.240 --> 0:09:44.719 evolved after we had corporate structure, which we couldn't have 0:09:44.840 --> 0:09:49.240 until we had specialized jobs. So my suspicion is that 0:09:49.280 --> 0:09:53.320 we will have new jobs that evolve as a result 0:09:53.360 --> 0:09:56.559 of the technology that we're building. Now, let's jump right 0:09:56.559 --> 0:10:00.280 into where we are in the modern economy. On the 0:10:00.320 --> 0:10:05.880 perspective of a big accounting and consulting firm, they split 0:10:05.920 --> 0:10:09.079 the two pieces into different groups. Is that right? So 0:10:10.120 --> 0:10:15.480 we have some regulatory requirements that create Chinese walls, and 0:10:15.760 --> 0:10:19.640 we there are a long list of advisory services that 0:10:19.679 --> 0:10:23.040 we cannot offer to our audit clients. Um. But this 0:10:23.120 --> 0:10:26.240 is a great business model because it diversifies our business. 0:10:26.320 --> 0:10:28.760 We have audit and tax um, and then we have 0:10:28.960 --> 0:10:32.360 our entire advisory business, which is very diverse. So we 0:10:32.440 --> 0:10:35.760 do things like data and analytics, we do things. We 0:10:35.800 --> 0:10:38.960 have an entire business called people and change, which when 0:10:38.960 --> 0:10:41.680 you think about what is happening in the labor force 0:10:42.120 --> 0:10:44.720 and the way technology is impacting firms and how they're 0:10:44.760 --> 0:10:48.280 managing for that, how they're retraining their workers. Um, that's 0:10:48.280 --> 0:10:51.079 a that's a huge practice for us. For example, so 0:10:51.160 --> 0:10:53.920 you of course risk compliance, all that other stuff that 0:10:54.280 --> 0:10:58.080 traditionally expect someone like KPMG to do so. You originally 0:10:58.160 --> 0:11:00.520 were on the buy side, You were in an investor 0:11:00.679 --> 0:11:04.960 in fixed income and alternative investments. How has that colored 0:11:05.280 --> 0:11:10.360 how you see, uh, the world of economics, whether it's 0:11:10.400 --> 0:11:14.680 for an audit slash consulting firm or anyone else. What 0:11:14.760 --> 0:11:19.080 does coming from the buy side due to your economic perspective? Well, 0:11:19.520 --> 0:11:23.480 for me, I think it's critical to my edge and 0:11:23.480 --> 0:11:25.760 and that is that I've spent most of my career 0:11:25.840 --> 0:11:29.280 using economics to make investment decisions and put money on 0:11:29.320 --> 0:11:33.360 the line. So that sort of classic UH saying I'd 0:11:33.400 --> 0:11:37.360 love to find a one handed economist. Right on the 0:11:37.400 --> 0:11:42.040 other hand, um and and certainly that that discipline I 0:11:42.040 --> 0:11:43.959 think is very important. And I think the other thing 0:11:44.000 --> 0:11:47.760 that it really um and that's sort of a chicken 0:11:47.760 --> 0:11:50.600 and egg thing. I noticed this about myself when I 0:11:50.679 --> 0:11:53.760 was at Chase. I noticed that I had an ability 0:11:53.800 --> 0:11:56.640 to do pattern recognition and see when there might be 0:11:56.679 --> 0:11:59.640 opportunities in the market as a result of either shifting 0:11:59.679 --> 0:12:03.760 market data or shifting economic data and matching those two 0:12:03.800 --> 0:12:06.719 together and doing analysis on them. So because I had 0:12:06.760 --> 0:12:10.360 this ability to see inflection points, it pushed me from 0:12:10.640 --> 0:12:13.960 the cell side at chase into the by side, and 0:12:14.280 --> 0:12:16.920 while I was at on the Bye side, that's really 0:12:17.440 --> 0:12:21.880 where I had my edge. And coming back into doing 0:12:22.200 --> 0:12:25.679 applied economics or business economics, I think when I go 0:12:26.000 --> 0:12:29.000 speak with either the leaders of our firm, our clients, 0:12:29.000 --> 0:12:32.640 when I write research, it's all oriented towards what is 0:12:32.640 --> 0:12:34.760 the inflection point we need to be paying attention to 0:12:35.160 --> 0:12:37.560 and how do you make money off of this inflection point. 0:12:37.640 --> 0:12:41.960 So let's address that precise topic. Where are we in 0:12:42.000 --> 0:12:45.480 the economic cycle today and where do you see the 0:12:45.520 --> 0:12:51.560 next inflection point coming, both in terms of sectors or chronology. Yeah, 0:12:52.040 --> 0:12:55.600 so we're in the happy part of the cycle, We're 0:12:55.640 --> 0:12:58.080 in the we're in the end of the cycle probably, 0:12:58.480 --> 0:13:03.200 Although with that said, I firmly believe UH expansions don't 0:13:03.200 --> 0:13:06.480 die of old age, right, they need to bump into something. 0:13:07.160 --> 0:13:11.480 And so we have had consecutive months and this consecutive 0:13:11.480 --> 0:13:14.120 is really important, consecutive months of jobs growth. If you 0:13:14.160 --> 0:13:18.080 look back over previous recoveries, that is a streak that 0:13:18.200 --> 0:13:24.680 is seventy longer than the previous record. So even though 0:13:25.000 --> 0:13:28.120 people aren't necessarily happy about the jobs mix that we 0:13:28.200 --> 0:13:30.800 have in the economy right now, that is still an 0:13:30.920 --> 0:13:36.000 unprecedented statistic, and it is allowed consumers to really feel 0:13:36.120 --> 0:13:38.480 very confident. We see that in the consumer confidence data. 0:13:38.840 --> 0:13:41.320 The consumer has been the backbone of the recovery. We 0:13:41.400 --> 0:13:44.679 haven't had as much investment, for example, as in previous recoveries, 0:13:45.120 --> 0:13:49.360 and so it's it's helping us sort of continue that 0:13:49.840 --> 0:13:53.600 consumption boom. But it's well founded. Household balance sheets are 0:13:53.600 --> 0:13:57.480 fairly healthy, right, we haven't um In fact, because of 0:13:57.520 --> 0:14:00.360 the crisis, we actually had a bit of a line 0:14:00.800 --> 0:14:04.040 in in debt for households, mostly in the in the 0:14:04.360 --> 0:14:07.880 housing sector. But it's allowed us to have sort of 0:14:07.880 --> 0:14:11.120 a balanced recovery for the most part. And so in 0:14:11.240 --> 0:14:15.000 terms of inflection points, at some point, I know people 0:14:15.000 --> 0:14:17.319 have been watching and waiting for this. I expect we're 0:14:17.320 --> 0:14:20.640 going to see some wage increases and we're seeing significant 0:14:20.640 --> 0:14:23.520 shortages in a very important sector and that is the 0:14:23.560 --> 0:14:28.720 construction sector. So the Associated General Contractors does a survey 0:14:28.840 --> 0:14:32.640 and there are a number of categories where over seventy 0:14:33.360 --> 0:14:36.280 of their respondents say they cannot find qualified workers and 0:14:36.280 --> 0:14:39.000 that they have to go ahead and raise wages. How 0:14:39.080 --> 0:14:42.280 much of that is related to the fact that during 0:14:42.280 --> 0:14:47.600 the financial crisis and during the housing collapse, a huge 0:14:47.680 --> 0:14:53.640 number of immigrants who were actually contractors, builders, electricians, plumbers, etcetera. 0:14:54.520 --> 0:14:58.120 All went home, went back to Mexico or wherever because 0:14:58.200 --> 0:15:01.200 the jobs weren't here. And so you created this void. 0:15:01.600 --> 0:15:05.640 The economy created this void in that segment of the 0:15:05.720 --> 0:15:08.800 labor force. So we lost about a million and a 0:15:08.840 --> 0:15:12.960 half construction jobs, and some of them were filled by immigrants, 0:15:12.960 --> 0:15:16.680 some of them were filled by native born individuals, and 0:15:16.800 --> 0:15:19.480 a lot of people started to do new things. They 0:15:19.520 --> 0:15:22.600 had to pivot to new careers, and they haven't been 0:15:22.680 --> 0:15:27.320 drawn back into the construction sector. Um. Another thing that 0:15:27.360 --> 0:15:29.440 we had during the housing boom is we had people 0:15:29.520 --> 0:15:32.320 forego higher education and just leave high school and go 0:15:32.720 --> 0:15:36.040 start doing construction because it was a career where you 0:15:36.040 --> 0:15:38.000 could make a fair amount of money towards the end 0:15:38.040 --> 0:15:42.080 of the boom. And and so those people, a lot 0:15:42.080 --> 0:15:44.960 of them went back to university after the crisis and 0:15:45.000 --> 0:15:48.120 then retooled themselves. If we get frothy enough again, if 0:15:48.160 --> 0:15:51.120 the if the price of labor goes up enough, you 0:15:51.120 --> 0:15:54.080 will draw people into that sector. The issue, of course, 0:15:54.120 --> 0:15:56.240 is that they won't have the skills, right, So some 0:15:56.320 --> 0:15:59.320 of these some of these jobs are our medium skilled 0:15:59.400 --> 0:16:02.080 jobs that you need to learn how to do a 0:16:02.160 --> 0:16:08.000 specialty where whether we're talking about electricians, plumbers, um carpenters, 0:16:08.040 --> 0:16:10.920 so you you can't just walk into that job. Now 0:16:10.960 --> 0:16:16.120 that we're ten years past the financial crisis, are things 0:16:16.400 --> 0:16:20.920 beginning to normalize in the world of economics, Yes, in 0:16:20.960 --> 0:16:24.280 a way, there's still a big mystery. So even though 0:16:24.320 --> 0:16:28.400 I expect some of the labor shortage data that we're seeing, 0:16:28.400 --> 0:16:31.320 whether it's National Federation of Independent Business or this associated 0:16:31.360 --> 0:16:34.280 General Contractors, some of this labor shortage I expect to 0:16:34.320 --> 0:16:38.280 eventually translate into wage increases. But I'll tell you, the 0:16:38.280 --> 0:16:40.160 FETE has been waiting for this for a long time. 0:16:40.280 --> 0:16:42.560 We have all been waiting for this for a long time, 0:16:43.000 --> 0:16:48.440 and there is some slack in the labor market still 0:16:48.440 --> 0:16:52.200 that that is um confusing. And I'll tell you why. 0:16:52.320 --> 0:16:54.200 Most people that have been out of the labor force 0:16:54.240 --> 0:16:57.520 for a period of time, they're not setting wages right, 0:16:57.800 --> 0:17:00.600 they're not the most desirable people to hire. They've had 0:17:00.680 --> 0:17:03.880 skills atrophy. They come back in generally if they come 0:17:03.920 --> 0:17:05.960 back in at a lower rage, and it's not We've 0:17:06.000 --> 0:17:08.960 had a pickup in the participation rate, but not to 0:17:09.040 --> 0:17:11.959 the point where you would really expect this portion of 0:17:12.000 --> 0:17:15.520 the labor force to be influencing wages, and so it 0:17:15.680 --> 0:17:19.200 is perplexing to me, it is perplexing to the Fed. 0:17:19.720 --> 0:17:23.000 Um Janet Yellen has called the lack of inflation and mystery. 0:17:23.080 --> 0:17:27.520 So we have normalized in some ways, but in this 0:17:27.680 --> 0:17:33.040 aspect of prices and whether um and and specifically related 0:17:33.080 --> 0:17:38.040 to wages we have we don't seem to have normalized. 0:17:38.640 --> 0:17:43.199 Although maybe we're all just misunderstanding the slack that's out there, 0:17:43.359 --> 0:17:46.240 or perhaps want a tipping point of higher wages, which 0:17:46.280 --> 0:17:49.440 I think in certain sectors is an absolute given. You've 0:17:49.440 --> 0:17:53.360 had a number of pretty high profile jobs in the 0:17:53.400 --> 0:17:58.840 world of finance. Does this tell us anything about women 0:17:58.840 --> 0:18:02.120 in finance? We know women have been let me man 0:18:02.160 --> 0:18:05.959 explain to you women in finance. We have very interested 0:18:05.960 --> 0:18:07.880 in what you have to say. Well, we know that 0:18:08.359 --> 0:18:11.040 women have not been promoted. There aren't as many women 0:18:11.520 --> 0:18:16.040 on the board level, at the sea level, uh, managing assets, etcetera. 0:18:16.240 --> 0:18:22.239 It's it's uh disproportionately a boys club, although there are 0:18:22.280 --> 0:18:25.200 signs that that's starting to change. Tell us a little 0:18:25.240 --> 0:18:28.120 bit about your career path and what it was like 0:18:29.000 --> 0:18:32.399 being a woman in a world where these were, for 0:18:32.440 --> 0:18:37.520 a long time traditionally male jobs. Well, I would say 0:18:37.520 --> 0:18:41.080 that I'm still in a very male dominated industry in general. 0:18:41.119 --> 0:18:45.800 Now at KPMG, we have a goal of having of 0:18:45.840 --> 0:18:51.560 our partners be women. And we're at twenty five now, 0:18:51.960 --> 0:18:57.560 so compared to Wall Street, that is definitely a better environment. 0:18:57.680 --> 0:19:01.800 And our CEO is a woman. We oh, Lynn Duddy 0:19:01.880 --> 0:19:04.840 is a woman. She's fabulous. She happens to be a woman. 0:19:04.880 --> 0:19:09.320 She's fabulous CEO and um. And so we've made a 0:19:09.320 --> 0:19:12.960 concerted effort. And the reason that's important, and the reason 0:19:13.040 --> 0:19:15.720 I think that it's taken so long in places like 0:19:15.760 --> 0:19:19.400 Wall Street that are male dominated, is that there's an 0:19:19.560 --> 0:19:22.880 natural in group bias, right, so we tend to hire 0:19:22.880 --> 0:19:25.399 people who look like us and who who act like 0:19:25.520 --> 0:19:28.000 us and I share the same interests and and so 0:19:28.200 --> 0:19:33.000 it's it's understandable, and it pervades everything. It pervades the 0:19:34.119 --> 0:19:38.159 recruiting practices. It also pervades what when you look at 0:19:38.200 --> 0:19:39.720 young women and they look out, well, what do I 0:19:39.800 --> 0:19:41.240 want to be when I grew up? Now, I was 0:19:41.320 --> 0:19:44.919 lucky I had My father was in finance, so he 0:19:45.080 --> 0:19:46.920 never had a bias that I shouldn't be in finance. 0:19:46.960 --> 0:19:48.440 In fact, he probably had a bias that I should 0:19:48.480 --> 0:19:52.359 be in finance, right, So so that I think gave 0:19:52.440 --> 0:19:57.840 me um an edge and uh and a unique perspective 0:19:57.880 --> 0:20:00.240 and approach that I never thought it was d that 0:20:00.280 --> 0:20:01.920 I would be in finance or that I would be 0:20:02.000 --> 0:20:05.080 very successful in finance. Michelle Myers, who's one of the 0:20:05.880 --> 0:20:10.639 senior economists at Merrill Lynch, specifically said at in the 0:20:10.640 --> 0:20:15.200 current environment, there are now women who are role models, 0:20:15.200 --> 0:20:19.320 whether it's real Seabird or Lizzie and Sanders at Schwab 0:20:19.480 --> 0:20:21.760 or there's a whole run of different absolutely women you 0:20:21.800 --> 0:20:25.840 can name, but go back at generation there really weren't 0:20:25.840 --> 0:20:28.120 a whole lot of role models for women who wanted 0:20:28.119 --> 0:20:29.760 to go to Wall Street. Well, let's focus on this 0:20:29.840 --> 0:20:32.439 because this issue of role models is really important and 0:20:32.480 --> 0:20:34.879 it's one of the things that's going to propel more women, 0:20:35.000 --> 0:20:37.359 and it's one of the reasons where you need a 0:20:37.480 --> 0:20:40.879 certain critical mass because if you were just the token woman, 0:20:41.680 --> 0:20:44.480 you don't get really from a firm perspective, you don't 0:20:44.480 --> 0:20:47.760 get necessarily all of the diversifying effects and all of 0:20:47.760 --> 0:20:51.040 the beneficial effects of having a more diverse perspective in 0:20:51.040 --> 0:20:53.840 your workplace. But once you hit a critical mass, let's 0:20:53.840 --> 0:21:00.000 say it's you start to have a very different um 0:21:00.080 --> 0:21:03.840 type of conversation around certain things. Your marketing appeals to 0:21:03.880 --> 0:21:09.200 a broader segment of the purchasing population. Uh, you just um, 0:21:09.480 --> 0:21:12.600 you tend to have less fraud. They are all sorts 0:21:12.680 --> 0:21:17.280 of definite advantages to having a greater mix of men 0:21:17.320 --> 0:21:20.840 and women in an organization. So since you've joined the 0:21:20.880 --> 0:21:25.600 world of finance, what improvements have been made towards achieving 0:21:25.840 --> 0:21:31.440 a better balance of males to females um in the workplace. So, 0:21:31.840 --> 0:21:34.119 certainly in the field of business economics now is different 0:21:34.119 --> 0:21:37.840 in academic economics. I was very fortunate to join the 0:21:37.920 --> 0:21:41.600 National Association for Business Economics as a young economist, and 0:21:41.840 --> 0:21:45.359 NAVE as it's called for short, has always had women 0:21:45.640 --> 0:21:49.840 leaders within the organization. So we had women presidents of NAVE, 0:21:50.119 --> 0:21:54.359 people like Maureen Haver who founded Haver Analytics, Diane Swank 0:21:54.520 --> 0:21:57.800 when she was the chief economist at Mazzaro. Uh, Ellen 0:21:57.880 --> 0:22:00.280 Hughes Cromwick who used to be the chief economy missed 0:22:00.280 --> 0:22:03.120 it Ford. Uh you know I could, I could list 0:22:03.240 --> 0:22:07.560 more right, and so that I saw these women who 0:22:07.560 --> 0:22:10.560 were chief economists as role models and that, and I 0:22:10.560 --> 0:22:15.040 saw women attending our meetings. Um, now when I have 0:22:15.280 --> 0:22:16.879 I have a young woman on my team who you 0:22:17.160 --> 0:22:19.400 who I brought into I said, you have to start 0:22:19.400 --> 0:22:21.080 at name. Young, You're going to learn so much it 0:22:21.080 --> 0:22:24.560 will be great. And to me, coming from Wall Street, 0:22:24.560 --> 0:22:26.359 I thought, well, Name is great because we probably have 0:22:27.040 --> 0:22:33.240 in the membership about women and in leadership probably about women. 0:22:33.320 --> 0:22:35.080 So people on the board of Name, people who are 0:22:35.080 --> 0:22:38.119 presidents of Name. And she's like, no, it's so she 0:22:38.240 --> 0:22:40.720 sees all men, whereas I see, Oh, my gosh, that's 0:22:40.720 --> 0:22:44.320 so much improvement because my frame of reference. So this 0:22:44.400 --> 0:22:46.919 makes me excited for a couple of reasons. One, I 0:22:46.960 --> 0:22:51.159 got to see progress too. It's obviously not yet and 0:22:51.200 --> 0:22:53.359 the next generation is going to make that happen. The 0:22:53.400 --> 0:22:57.080 fact that it's women, they look at its oh, this 0:22:57.119 --> 0:23:00.400 isn't remotely what it Maybe it's thirty five, but still 0:23:00.600 --> 0:23:04.560 compared with twenty years ago, it's miles ahead. And the 0:23:04.600 --> 0:23:06.960 fact that it's looked at as oh, they're not getting 0:23:06.960 --> 0:23:10.920 this done is pretty that's pretty amazing. So we now 0:23:11.000 --> 0:23:15.760 have men who are feminists and and mainstream men people 0:23:15.800 --> 0:23:19.600 like Justin Trudeau, who's the Prime Minister of Canada. Right, 0:23:19.680 --> 0:23:21.880 and now I've heard I've heard more and more men 0:23:22.359 --> 0:23:26.399 say I'm a feminist. And and the thing is is 0:23:26.440 --> 0:23:29.320 that it takes both men and women to make this happen. 0:23:29.359 --> 0:23:33.439 It takes us working together. This isn't just a woman's cause. 0:23:34.040 --> 0:23:36.960 And it's not even just a men of men who 0:23:36.960 --> 0:23:41.000 are fathers of daughters cause. Right. It benefits everybody. And 0:23:41.080 --> 0:23:43.400 so the more men that can get out there and say, yeah, 0:23:43.400 --> 0:23:47.639 I'm also a feminist, it benefits them. It benefits them financially, 0:23:47.680 --> 0:23:50.959 it benefits them socially, and we're starting to see that 0:23:51.000 --> 0:23:53.080 more and more. Let me ask you a question that 0:23:53.119 --> 0:23:56.000 will give the compliance people at KPMG a heart attack, 0:23:56.359 --> 0:24:00.240