WEBVTT - The Top 10 Things We Learned on Odd Lots in 2023 0:00:10.080 --> 0:00:13.680 Hello, and welcome to another episode of the Odd Lots podcast. 0:00:13.760 --> 0:00:16.079 I'm Jill Wisenthal and I'm Tracy Alloway. 0:00:16.239 --> 0:00:19.319 Tracy, obviously, one of the best things of doing odd 0:00:19.360 --> 0:00:22.959 loss is just all the random fun things that we learned. 0:00:22.960 --> 0:00:25.119 I mean that you know, that we learn over the 0:00:25.120 --> 0:00:26.800 course of the year, or that we learn in any 0:00:26.800 --> 0:00:27.520 given episode. 0:00:27.680 --> 0:00:27.880 Yeah. 0:00:27.920 --> 0:00:30.520 I don't know of many other jobs where you can 0:00:30.600 --> 0:00:33.840 just kind of look into anything that you think might 0:00:33.880 --> 0:00:36.839 be interesting, but this is one of them. And on 0:00:36.920 --> 0:00:39.440 all thloughts, I suppose we do have a reputation nowadays 0:00:39.440 --> 0:00:43.559 for covering a wide variety of topics, so things that 0:00:43.600 --> 0:00:45.919 are going on right now, things that may have happened 0:00:46.000 --> 0:00:49.080 in the past, And it means that we learn a 0:00:49.120 --> 0:00:51.320 lot about a wide variety of. 0:00:51.360 --> 0:00:54.040 Subjects, and some of them, of course are you know, 0:00:54.080 --> 0:00:56.160 we learn about them, and the you know, what we 0:00:56.320 --> 0:01:01.760 learned is interesting but also sort of straightforward. So for example, 0:01:01.920 --> 0:01:05.920 you know, I'm not surprised that an increase in steel costs, 0:01:06.040 --> 0:01:09.400 although that's interesting, makes it harder to build offshore wind 0:01:09.800 --> 0:01:13.440 but I was surprised to learn, for example, that the 0:01:13.560 --> 0:01:17.959 Jones Act, perpetual oddlote topic was also an impediment also interesting, 0:01:18.040 --> 0:01:20.760 also very surprising in a way I was definitely not anticipating. 0:01:20.920 --> 0:01:23.600 Yes, it all comes back to the Jones Act. This 0:01:23.680 --> 0:01:25.760 is sort of a classic all thoughts thing where we 0:01:26.040 --> 0:01:29.000 discover one aspect of the world or the economy, and 0:01:29.040 --> 0:01:33.000 then we keep discovering it in other conversations. It keeps 0:01:33.040 --> 0:01:35.479 coming up. But it is the end of the year 0:01:36.120 --> 0:01:39.280 and we are both in a reflective mood, and so 0:01:39.400 --> 0:01:42.120 we've gone over all the conversations that we had in 0:01:42.200 --> 0:01:45.120 twenty twenty three and we've picked out our top ten 0:01:45.440 --> 0:01:49.280 most interesting and most surprising things that we have learned 0:01:49.280 --> 0:01:49.680 this year. 0:01:50.040 --> 0:01:50.280 Yep. 0:01:50.400 --> 0:01:53.240 So let's kick it straight off with an episode with 0:01:53.360 --> 0:01:56.760 a Josh Younger on the origin of euro dollars. 0:01:57.040 --> 0:01:59.480 So the first the definition of the euro dollar being 0:01:59.480 --> 0:02:02.760 deployed off sure is fairly specific, and the question is 0:02:02.800 --> 0:02:06.120 when did that start, and we don't really know. We 0:02:06.200 --> 0:02:09.720 know roughly in the late forties to declassified CIA documents. 0:02:09.760 --> 0:02:12.160 After the war ended, the Russians were moving money around 0:02:12.160 --> 0:02:14.400 because they were worried about a subsequent land war in 0:02:14.440 --> 0:02:16.360 Europe and they didn't want their funds to be frozen. 0:02:16.560 --> 0:02:19.119 Never mind the weirdness of like a Soviet invasion where 0:02:19.120 --> 0:02:21.240 they need dollars. I'm not sure why that would be necessary, 0:02:21.240 --> 0:02:23.640 but they were uncomfortable leaving money in New York and 0:02:23.680 --> 0:02:25.760 so there were a handful. 0:02:25.360 --> 0:02:28.320 Title of this episode should be the Communist origins of 0:02:28.480 --> 0:02:29.799 euro dollars area. 0:02:30.040 --> 0:02:33.440 Yeah, and so there were a sanctions which which connects 0:02:33.440 --> 0:02:36.080 somewhat to today, and they moved their money from New 0:02:36.160 --> 0:02:39.760 York banks to a handful of banks to specifically in France, London, 0:02:39.840 --> 0:02:43.160 and Belgium, because the local regulations allowed those banks to 0:02:43.160 --> 0:02:46.240 issue non local currency deposits. Your local regular has to 0:02:46.240 --> 0:02:49.400 allow this in the first instance. And in Paris in particular, 0:02:49.760 --> 0:02:52.320 there was a bank called basically the Commercial Bank of 0:02:52.320 --> 0:02:53.760 Northern Europe. I'm not going to try to pronounce it 0:02:53.800 --> 0:02:56.239 in French, but it was called Bison. Bison was run 0:02:56.280 --> 0:02:59.200 by a notorious Communist sympathizer who had relationships in Moscow, 0:02:59.720 --> 0:03:03.320 and so they were comfortable with that particular bank, and 0:03:03.360 --> 0:03:05.720 they grew its assets from seven million dollars to two 0:03:05.800 --> 0:03:09.079 hundred million dollars over a few years. The first recorded 0:03:09.200 --> 0:03:12.119 use of those euro dollars was possibly, although it's hard 0:03:12.120 --> 0:03:15.320 to say, replacing the salaries of striking French coal miners 0:03:16.320 --> 0:03:19.320 forty eight. So there's some evidence of that, But that's 0:03:19.360 --> 0:03:21.920 not really a euro dollar in the definition that I 0:03:22.120 --> 0:03:24.840 just described, because it doesn't really have a use because 0:03:24.840 --> 0:03:27.600 I didn't say anything about the asset side of the equation. 0:03:28.360 --> 0:03:30.440 So where did the asset side come from? This is 0:03:30.480 --> 0:03:32.000 just going to be one of those episodes where we 0:03:32.080 --> 0:03:34.440 ask you, like, how did this happen? 0:03:36.240 --> 0:03:38.920 So it was tied basically to trade because trade was 0:03:38.960 --> 0:03:41.920 denominated in dollars, but when it's all Communist dollars, it 0:03:41.960 --> 0:03:44.120 has to be east west trades. So trade crossing the 0:03:44.120 --> 0:03:47.560 Iron Curtain, which was small because both the Russians and 0:03:47.560 --> 0:03:50.360 the Americans were not terribly comfortable with a large volume 0:03:50.760 --> 0:03:52.840 of trade, and the Russians in particular had a policy 0:03:52.840 --> 0:03:55.200 of self reliance, so they said, we don't want to 0:03:55.280 --> 0:03:59.200 need imports from the West to run our economy or 0:03:59.200 --> 0:04:01.560 a society. We don't know how big that was. It 0:04:01.600 --> 0:04:04.200 was actually, as of nineteen forty seven, illegal to talk 0:04:04.240 --> 0:04:07.200 about economic data in the Soviet Union. It was a 0:04:07.280 --> 0:04:09.760 lot passed. It said, this is like punishable by some 0:04:09.920 --> 0:04:12.040 extreme measure. Oh wow, So we don't actually know the 0:04:12.120 --> 0:04:14.640 volume of this trade, but there's some evidence that it 0:04:14.720 --> 0:04:17.000 was there, that it was funded in part by like 0:04:17.080 --> 0:04:20.200 trade finance was facilitated by BSEN to some extent. It's 0:04:20.279 --> 0:04:23.840 unclear when it started, but it's a very small market. 0:04:24.920 --> 0:04:28.320 The surprising communist origins of euro dollars, that's sort of 0:04:28.520 --> 0:04:31.440 not only a classic Old Blots topic, but a sort 0:04:31.480 --> 0:04:34.360 of classic line from one of our favorite guests, Josh Younger. 0:04:34.680 --> 0:04:36.280 Not that I'm thinking about it, were other Remember we 0:04:36.360 --> 0:04:38.200 learned that there was euro dollars gum? 0:04:38.920 --> 0:04:42.040 Oh yeah, yeah, I went looking for a foot well. 0:04:42.200 --> 0:04:44.719 I went on eBay to see if anyone was selling 0:04:44.839 --> 0:04:47.560 gum from the nineteen seventies with this packaging. I could 0:04:47.560 --> 0:04:48.000 not find it. 0:04:48.080 --> 0:04:51.040 But that was a great episode for many new and 0:04:51.200 --> 0:04:52.119 surprising things. 0:04:52.440 --> 0:04:56.320 Yes, now, speaking of new and surprising things, another thing 0:04:56.640 --> 0:04:58.800 we learned had to do with the sort of hidden 0:04:59.200 --> 0:05:05.320 connection within economies and how economies evolve. And we spoke 0:05:05.360 --> 0:05:09.680 to Ricardo Housman of the Center for International Developments Growth 0:05:09.760 --> 0:05:13.720 Lab at Harvard University, and we talked to him about 0:05:13.720 --> 0:05:18.320 how economies actually develop their complexity. He gave us a 0:05:18.360 --> 0:05:22.679 really unexpected example of how that works. Take a listen. 0:05:23.200 --> 0:05:27.080 A lot of increase in complexity in Japan and Korea 0:05:27.560 --> 0:05:30.920 did not happen because new companies were created to do 0:05:31.000 --> 0:05:35.560 more things, but because established companies, these chiballs in Korea, 0:05:35.640 --> 0:05:40.120 these k etsuos in Japan, divers fight internally into more things. 0:05:40.520 --> 0:05:45.160 So a company like Samson started in sugar trading, and 0:05:45.240 --> 0:05:49.080 you know now they are the largest producer of semiconductors 0:05:49.080 --> 0:05:53.719 and sgrams and TV screens and smartphones. That process of 0:05:53.760 --> 0:05:57.919 transformation happened inside the company, and it happened by adding 0:05:58.360 --> 0:06:02.320 capabilities to their capability. So for example, you'd say Finland 0:06:02.400 --> 0:06:05.120 is a country that had a lot of trees, and 0:06:05.279 --> 0:06:08.520 traditional development economists would have said, cut those trees and 0:06:08.560 --> 0:06:11.320 sell wood. And then they would say, no, don't sell wood. 0:06:11.720 --> 0:06:14.679 Make furniture with that wood, or make paper with that wood. 0:06:14.839 --> 0:06:18.080 Add value to your raw materials. But that's not where 0:06:18.120 --> 0:06:20.960 the story really went. It's sort of like Finland had 0:06:20.960 --> 0:06:22.840 a lot of trees, so they have to cut the trees. 0:06:22.880 --> 0:06:25.960 But to cut the trees, you need tools to cut trees. 0:06:26.000 --> 0:06:29.200 You need machines to cut trees. So they became good 0:06:29.200 --> 0:06:32.200 at tools and machines that cut wood, and from there 0:06:32.400 --> 0:06:35.560 they moved to tools and machines that cut because not 0:06:35.640 --> 0:06:37.720 everything is made out of wood. And from there they 0:06:37.760 --> 0:06:42.080 made they went to automated machines that cut, because cutting 0:06:42.080 --> 0:06:45.320 everything by hand can be either boring or imprecise. And 0:06:45.360 --> 0:06:48.360 then they said, you know, from automated machines that cut, 0:06:48.400 --> 0:06:50.720 they want to just automated machines. Why do we need 0:06:50.760 --> 0:06:53.400 to cut? There's more to life than just cutting, right, 0:06:53.880 --> 0:06:57.400 And then from automated machines they ended up in Nokia. 0:06:59.000 --> 0:07:02.480 So the process is a process of adding capabilities to 0:07:02.560 --> 0:07:05.839 their capabilities, because once you know how to do something, 0:07:06.320 --> 0:07:09.680 there is something in that cognitive vicinity that you could do. 0:07:11.200 --> 0:07:13.840 There's more to life than just cutting. It's got to 0:07:13.840 --> 0:07:16.560 be like a great it's true, right, I never thought 0:07:16.600 --> 0:07:18.600 about it, but it's definitely true. There's more to life 0:07:18.600 --> 0:07:19.200 than just cutting. 0:07:19.360 --> 0:07:23.960 Also, Ricardo's analogy of monkeys swinging from trees as an 0:07:24.000 --> 0:07:27.720 economic metaphor that lives, that imagery lives free in my 0:07:27.880 --> 0:07:28.960 head for all time. 0:07:29.080 --> 0:07:31.480 But yeah, that was a great conversation, and thinking about 0:07:31.520 --> 0:07:34.520 how economies actually develop in terms as opposed to how 0:07:34.520 --> 0:07:38.280 you might expect them to develop on paper was really great. 0:07:38.280 --> 0:07:40.800 All right, speaking of the sort of you know, I 0:07:40.840 --> 0:07:44.160 guess we're going to speak on the complexity theme for 0:07:44.240 --> 0:07:47.480 the moment. So with Ricardo, we talked about complexity in 0:07:47.560 --> 0:07:50.760 terms of it's good that countries get more complex with 0:07:50.800 --> 0:07:54.320 their economic development, but complexity it can also be bad 0:07:54.760 --> 0:07:56.640 in some respects. And one area is that sort of 0:07:56.640 --> 0:07:59.880 famously complex is any time we're dealing with government soft 0:08:00.640 --> 0:08:04.040 and so. On this episode we spoke with Jennifer Palka 0:08:04.120 --> 0:08:08.400 and Dave Guarino, who at longtime veterans working on government software. 0:08:08.440 --> 0:08:12.000 I think anyone who knows about government software government websites 0:08:12.000 --> 0:08:16.000 probably no feels intuitively that they're more frustrating than to say, 0:08:16.360 --> 0:08:18.080 you know, the website that you might use for a 0:08:18.120 --> 0:08:20.680 bank or buying an airline ticket or something like that. 0:08:21.080 --> 0:08:23.480 So we're going to hear the story of a software 0:08:23.680 --> 0:08:26.480 system that was so bad even the designer didn't believe 0:08:26.720 --> 0:08:28.240 or couldn't believe it wasn't working. 0:08:28.520 --> 0:08:32.120 When we were at California, State of California working on 0:08:32.200 --> 0:08:35.599 unemployment insurance, they were actually about to put out a 0:08:35.920 --> 0:08:39.680 Business System Modernization RFP. Actually I think about it to 0:08:39.679 --> 0:08:41.880 award it to a vendor, and I think it had 0:08:42.000 --> 0:08:45.200 seven six seven hundred requirements. We can check that, but 0:08:45.200 --> 0:08:48.720 it's in that's really a normal number of requirements, and 0:08:48.800 --> 0:08:51.280 so they do all these things that where you can 0:08:51.360 --> 0:08:53.800 check a box, but what they don't do is actually 0:08:53.880 --> 0:08:56.920 check that it works. So I mean, maybe I'll just 0:08:56.920 --> 0:08:58.760 tell a quick story from the book. And you know, 0:08:58.800 --> 0:09:03.760 there was famously this application for veterans' healthcare benefits at 0:09:03.760 --> 0:09:08.560 the VA that didn't work outside the building and they 0:09:09.400 --> 0:09:12.760 couldn't see it. So basically, somewhere in the specs it 0:09:12.840 --> 0:09:16.280 had that this form needed to work on a very 0:09:16.320 --> 0:09:21.440 specific and outdated combination of Internet Explorer and Adobe Reader. 0:09:22.040 --> 0:09:24.120 And the reason no one knew that it didn't work 0:09:24.160 --> 0:09:26.360 inside the building is that's how all the computers in 0:09:26.400 --> 0:09:28.800 there were set up. But if you were outside the 0:09:28.800 --> 0:09:32.079 building and had any other possible combination of those two 0:09:32.080 --> 0:09:34.640 pieces of software, it literally wouldn't load. And so they 0:09:34.640 --> 0:09:38.679 had very very few people applying for these benefits online, 0:09:39.200 --> 0:09:42.160 and you know, veterans were really, really, really frustrated, and 0:09:42.200 --> 0:09:46.000 it took a team going out there recording a veteran 0:09:46.160 --> 0:09:48.920 who had tried to do this dozens and dozens of times, 0:09:49.400 --> 0:09:53.640 bringing that video back and showing it to the Deputy 0:09:53.640 --> 0:09:55.880 secretary for them to be able to say, oh, okay, 0:09:55.880 --> 0:09:59.280 actually there is something to be fixed here. Okay, you know, 0:09:59.320 --> 0:10:01.000 you can go ahead and make a new form. But 0:10:01.080 --> 0:10:04.000 up to them, they said, sorry, it's fine, we're looking 0:10:04.040 --> 0:10:06.960 at the requirements. The requirements have been met. There's technically 0:10:07.000 --> 0:10:07.720 nothing wrong. 0:10:08.320 --> 0:10:10.839 That's amazing. It's also kind of crazy to think that 0:10:10.920 --> 0:10:13.080 people would have been looking at that and just been like, oh, well, 0:10:13.120 --> 0:10:16.400 I guess demand for veterans benefits is lower than we 0:10:16.480 --> 0:10:18.640 thought it would be. But actually it was a tech issue. 0:10:18.679 --> 0:10:21.160 I think what they said was demand for them doing 0:10:21.160 --> 0:10:24.040 it online is low. These veterans must not have access, 0:10:24.080 --> 0:10:26.079 which is absolutely not true, or they can't figure out 0:10:26.080 --> 0:10:28.080 the computer when in factive. Yeah, I mean the other 0:10:28.240 --> 0:10:30.520 telling them didn't figure out the software. They would tell them, 0:10:30.559 --> 0:10:32.840 And they told this guy Dominic, the veteran that they interviewed, 0:10:32.840 --> 0:10:35.040 they kept telling him it's user error. There's something wrong 0:10:35.080 --> 0:10:35.320 with you. 0:10:37.400 --> 0:10:39.680 That is still such a funny story. There are so 0:10:39.679 --> 0:10:42.720 many layers to it, so including the idea of people 0:10:42.760 --> 0:10:45.079 having to go out and shoot a video of a 0:10:45.200 --> 0:10:48.680 veteran trying to access this form and then bringing it 0:10:48.720 --> 0:10:50.840 back to someone who would watch it and be like, oh, okay, 0:10:50.880 --> 0:10:53.080 I see there is in fact a problem. But also 0:10:53.200 --> 0:10:57.560 that anecdote at the beginning about designing one piece of 0:10:57.720 --> 0:11:03.600 software for unemployment insurance with six thousand, seven hundred requirements, Like, 0:11:03.679 --> 0:11:07.079 how long does it take you to physically tick six thousand, 0:11:07.120 --> 0:11:09.360 seven hundred boxes? Is there an actual form where you 0:11:09.440 --> 0:11:11.520 have to go and like click every one of them? 0:11:11.559 --> 0:11:13.440 And how do you prove? Yeah, how do you prove 0:11:13.480 --> 0:11:15.640 that you did every single one? To the to the 0:11:15.720 --> 0:11:17.199 lawmakers that made that rule. 0:11:17.440 --> 0:11:22.840 Yeah, it sounds like, to your point, a very complex process. Say, 0:11:39.640 --> 0:11:42.360 this might be a little bit more simple, but I 0:11:42.400 --> 0:11:45.760 think it's generally accepted that in the world of commodities 0:11:45.880 --> 0:11:50.320 there is a fraud problem, and I think having lots 0:11:50.360 --> 0:11:54.520 of physical things that you're moving around poses an opportunity 0:11:54.559 --> 0:11:58.319 for criminals to take advantage of that process. We like 0:11:58.480 --> 0:12:02.240 to talk about financial fraud and crime on this podcast, 0:12:02.440 --> 0:12:06.400 and we saw a lot of instances recently of frauds 0:12:06.400 --> 0:12:11.199 happening in the commodity space, and specifically with one commodity 0:12:11.440 --> 0:12:15.240 in particular, and that is Nickel. So we wanted to 0:12:15.280 --> 0:12:18.600 know what is it about Nickel that makes it prone 0:12:19.240 --> 0:12:23.240 to fraud? And we brought on Anton Posner and Margo Brock, 0:12:23.320 --> 0:12:26.880 the CEO and president respectively of Mercury Group, and they 0:12:26.880 --> 0:12:30.280 came on and explained why there is so much financial 0:12:30.320 --> 0:12:31.800 crime tied to Nickel. 0:12:32.320 --> 0:12:34.559 It just to be clear on Nickel, and I think 0:12:34.600 --> 0:12:37.000 this is something Terry Duffy when we talk to him, 0:12:37.000 --> 0:12:39.439 he's like, there's something about nickel. It's that it's in bags, right, 0:12:39.520 --> 0:12:41.640 Like some metal is like stacked, you see it, and 0:12:41.679 --> 0:12:46.440 so everything What would be an ideal form of auditing. 0:12:46.520 --> 0:12:48.480 I can imagine like you open every bag, but like 0:12:48.520 --> 0:12:50.559 what is okay? 0:12:50.679 --> 0:12:55.840 Yeah, again, it becomes that randomized audit, that randomized sampling, 0:12:55.920 --> 0:12:58.520 and you do have to you have to look and 0:12:58.559 --> 0:13:01.000 you have to go in and say, let's you know, 0:13:01.040 --> 0:13:03.199 it's all stacked in the warehouse, let's break some down, 0:13:03.280 --> 0:13:06.120 let's pull it out, and let's just at a minimum 0:13:06.280 --> 0:13:07.880 open the top of the bags and look in. 0:13:09.720 --> 0:13:12.480 Also is going to say two Nichol is a much 0:13:12.520 --> 0:13:18.440 more higher value metal versus aluminum or zinc. So it's 0:13:18.559 --> 0:13:21.240 like counterfeiting. If you're going to counterfeit bills, you can 0:13:21.280 --> 0:13:23.880 probably counterfeit if taking the time to do it, you're 0:13:23.880 --> 0:13:25.800 going to be doing one hundred dollars bills, right, Rather 0:13:25.840 --> 0:13:29.360 than focusing on counterfeiting dollar bills, right, Nickel. 0:13:29.600 --> 0:13:34.240 So in bags high value, and there's really been two 0:13:34.320 --> 0:13:38.160 different types of fraud on it, and one is the 0:13:38.160 --> 0:13:42.280 Indian one that traffic Wor is involved in is during shipment, 0:13:42.640 --> 0:13:46.520 so by the time it lands where it's headed, the 0:13:46.640 --> 0:13:50.199 last containers are already afloat and everything, all the documents 0:13:50.200 --> 0:13:53.360 are presented and everyone's been paid, so they haven't had 0:13:53.400 --> 0:13:56.440 the opportunity to open doors on that very first container 0:13:56.480 --> 0:13:58.920 that's shipped to even look and find their fraud. 0:13:59.240 --> 0:14:00.520 So that fraud you have to. 0:14:00.480 --> 0:14:05.599 Really concentrate on combating at load. And then there's the 0:14:05.679 --> 0:14:08.360 fraud of the rocks that were in the nickel bags, 0:14:08.880 --> 0:14:11.680 and that was in warehouse for years and years, but 0:14:11.760 --> 0:14:16.000 again nobody, nobody opened up the bags there. So there's 0:14:16.240 --> 0:14:18.559 you know, like Anton said, it's a system as old 0:14:18.600 --> 0:14:21.040 as time, and there's so many points within that system 0:14:21.040 --> 0:14:24.520 where fraud can happen and theft happens, and the opportunities 0:14:24.560 --> 0:14:25.440 present themselves. 0:14:26.800 --> 0:14:29.480 To your point, Tracy introducing that, you know, I think 0:14:29.480 --> 0:14:31.680 one thing with commodities too, and something we talked about 0:14:31.680 --> 0:14:35.120 with Javier Blass, like it really does feel like the 0:14:35.240 --> 0:14:37.880 Last Wild West part. Yes, fine, it I mean I 0:14:37.880 --> 0:14:41.320 guess crypto kind of too. Also also a place where 0:14:41.320 --> 0:14:43.960 there's been some fraud I've heard, but any you know, 0:14:44.000 --> 0:14:46.080 it feels like, you know, a rock is a rock 0:14:46.200 --> 0:14:48.400 in a way that in a way that a digital 0:14:48.520 --> 0:14:51.640 claim to a company's cash flow is just much more 0:14:51.640 --> 0:14:52.360 easier to track. 0:14:52.640 --> 0:14:57.200 There's something almost pleasingly old fashioned about someone like taking 0:14:57.200 --> 0:14:59.720 a bag of rocks and painting them and then putting 0:14:59.720 --> 0:15:02.320 them back in the bag and tricking auditors that way. 0:15:02.440 --> 0:15:05.720 It's kind of it's satisfying in its simplicity, and. 0:15:05.680 --> 0:15:08.280 It still works in twenty twenty three because people still 0:15:08.320 --> 0:15:10.960 need bags of nickel and they can't check every bag. 0:15:11.120 --> 0:15:14.080 All right, let's pivot a little bit. So obviously, you know, 0:15:14.120 --> 0:15:16.680 we talk about finance of all different swords. We talk 0:15:16.720 --> 0:15:20.200 about real estate a lot on the show. One area 0:15:20.240 --> 0:15:23.080 that we haven't we've started talking about it more, but 0:15:23.120 --> 0:15:26.320 we want to do more on is insurance and just 0:15:26.360 --> 0:15:29.680 the explosion that a lot of real estate developers have 0:15:29.760 --> 0:15:33.040 seen in their insurance costs over the last year. Often 0:15:33.400 --> 0:15:35.600 a lot of it related to climate, but other factors 0:15:35.640 --> 0:15:38.640 also the law. Take a listen to David O'Reilly. He's 0:15:38.680 --> 0:15:42.560 the CEO of Howard Hughes, major real estate developer, with 0:15:42.680 --> 0:15:45.760 some shocking statistics about the price of insurance. 0:15:46.960 --> 0:15:50.560 Rates have taken off over the past year at ways 0:15:50.600 --> 0:15:53.360 that we've never experienced, and I've never seen in twenty years, 0:15:53.840 --> 0:15:55.920 and I'm told there's a lot of reasons for that. Yeah, 0:15:55.960 --> 0:15:59.120 the reinsurance market is drying up. People are reluctant to 0:15:59.160 --> 0:16:03.200 take risk, have been more and more natural disasters, making 0:16:03.240 --> 0:16:07.240 it harder and harder to price insurance appropriately, and there's 0:16:07.400 --> 0:16:09.800 just fewer and fewer risk takers on the other side 0:16:09.800 --> 0:16:12.640 of the table to meet the demand of folks that 0:16:12.760 --> 0:16:14.240 need insurance on this side of the table. 0:16:14.360 --> 0:16:16.240 When you say rates are taking off like the way 0:16:16.280 --> 0:16:18.360 you've never seen, can you like put some numbers behind 0:16:18.400 --> 0:16:21.000 it in terms of just like how different, how crazy 0:16:21.080 --> 0:16:22.880 is the market or the movement the rate of change 0:16:22.880 --> 0:16:25.400 in the market in twenty twenty three versus a period 0:16:25.440 --> 0:16:26.160 that it might be. 0:16:27.480 --> 0:16:30.720 Most risk managers would define insurance markets as either hardening 0:16:30.760 --> 0:16:32.320 or softening okay, worse or getting better. 0:16:32.520 --> 0:16:32.760 Okay. 0:16:33.000 --> 0:16:35.360 Every year they always tell me it's hardening, okay, and 0:16:35.440 --> 0:16:36.920 I say, one of these days it's going to soften, 0:16:36.960 --> 0:16:39.840 and sometimes it'll soften, but they always manage my expectations 0:16:39.880 --> 0:16:42.120 by saying it's hardening. Okay, So this year they said 0:16:42.120 --> 0:16:43.720 it's hardening, and I kind of rolled my eyes and 0:16:43.720 --> 0:16:46.680 shrugged and said, okay, here we go again, and we'll suck. 0:16:46.880 --> 0:16:48.520 You know, we'll take it. We'll take a three to 0:16:48.600 --> 0:16:49.640 five percent increase. 0:16:50.040 --> 0:16:50.920 Yeah, it'll be all right. 0:16:51.440 --> 0:16:53.880 And we came back with twenty five percent. Oh wait, 0:16:54.000 --> 0:16:57.080 maybe it's forty percent. And then some of our peers 0:16:57.120 --> 0:16:58.400 and some of those that I've talked to in the 0:16:58.400 --> 0:17:02.240 industry have seen a fifty percent And it's just there's 0:17:02.320 --> 0:17:04.760 not as much availability as there used to be, and 0:17:04.840 --> 0:17:08.760 then therefore certain pieces of the insurance stack gets more 0:17:08.800 --> 0:17:12.400 expensive for a company like Howard to use. With six 0:17:12.520 --> 0:17:15.480 billion of total insurable value. We do what's called the 0:17:15.520 --> 0:17:18.600 shared and layer program like most people do, which is 0:17:18.720 --> 0:17:21.240 think of a CMBs loan or an ABS loan, where 0:17:21.240 --> 0:17:23.760 you take the whole loan and you slice it by risk, 0:17:24.240 --> 0:17:26.199 and then you have this tetris like grid and you 0:17:26.280 --> 0:17:28.280 fill it up with insurers. Those that want to take 0:17:28.280 --> 0:17:30.160 the most risk at the top get the highest rate, 0:17:31.480 --> 0:17:32.840 and then all of a sudden, at the end of 0:17:32.880 --> 0:17:34.720 the year, when you go to get your policy there's 0:17:34.760 --> 0:17:37.920 a big gap in the middle, or you can't fill 0:17:37.960 --> 0:17:40.840 a couple of layers, and then the cost of filling 0:17:40.840 --> 0:17:44.399 those incremental layers are so pricey that it impacts the 0:17:44.440 --> 0:17:48.439 pricing of every layer around it. And it's just that 0:17:48.440 --> 0:17:50.880 there's not enough supply to meet the demand. 0:17:52.520 --> 0:17:57.320 So the insurance conversation is interesting on so many levels. 0:17:57.359 --> 0:18:00.760 So not only are rates increasing, so the costs are 0:18:00.760 --> 0:18:04.920 being passed on, making real estate more expensive for normal people, 0:18:04.960 --> 0:18:08.960 but there's also the pricing of financial risk and event risk, 0:18:09.040 --> 0:18:11.720 So how do you actually put a number on something 0:18:11.800 --> 0:18:14.600 like a flood or a hurricane. That is always fascinating. 0:18:15.040 --> 0:18:18.280 There's the distribution of risk, which David was talking about, 0:18:18.280 --> 0:18:21.560 the idea that okay, you can sell some tranches of risk. 0:18:21.640 --> 0:18:25.480 There's certain demand for like the lowest level of risk 0:18:25.560 --> 0:18:27.719 or the highest level of risk, but sometimes the in 0:18:27.760 --> 0:18:31.919 between spaces are becoming more difficult. And then there's also 0:18:32.400 --> 0:18:35.159 this big question which I think Joe, you and I 0:18:35.160 --> 0:18:37.879 have spoken about this before, but in a world where 0:18:38.000 --> 0:18:42.159 one off events are happening more often, where stuff in 0:18:42.200 --> 0:18:45.200 general is just perceived to be riskier than it was previously, 0:18:45.600 --> 0:18:49.919 the insurance companies kind of become the arbiters of accepted 0:18:50.320 --> 0:18:54.440 behavior and normality. They're the ones kind of putting standards 0:18:54.480 --> 0:18:57.000 in place by deciding whether or not they're going to 0:18:57.280 --> 0:19:01.879 ensure those particular practices. And I just that completely fascinating, totally. 0:19:01.920 --> 0:19:02.119 You know. 0:19:02.160 --> 0:19:04.600 The other thing that's interesting is we always talk about 0:19:04.640 --> 0:19:09.119 financial conditions and financial conditions tightening, loosening and higher rates 0:19:09.119 --> 0:19:12.480 and higher spreads, et cetera. But you never really hear 0:19:12.720 --> 0:19:16.919 insurance rates folded into the financial conditions convo. But you 0:19:17.000 --> 0:19:20.200 just have to assume that when insurance prices for certain 0:19:20.240 --> 0:19:23.320 projects jump thirty forty fifty percent in a year, they're 0:19:23.359 --> 0:19:25.440 just going to be many things that don't pencil out. 0:19:25.520 --> 0:19:28.040 So it feels to me like that's probably a massive 0:19:28.080 --> 0:19:30.280 tightening at least in twenty twenty three, or parts of 0:19:30.320 --> 0:19:33.480 twenty twenty three and twenty twenty two, tightening of financial 0:19:33.480 --> 0:19:36.439 conditions that perhaps wasn't captured in a lot of the metrics. 0:19:36.480 --> 0:19:39.040 Yeah, that's a good point, and Bloomberg does have a 0:19:39.080 --> 0:19:42.040 financial conditions index, so maybe we should suggest that they 0:19:42.080 --> 0:19:46.480 incorporate it somehow. Anyway, Speaking of costs going up in 0:19:46.520 --> 0:19:49.760 real estate, another surprising thing that happened this year at 0:19:49.840 --> 0:19:52.840 least to many people who perhaps didn't listen to all 0:19:52.880 --> 0:19:56.679 blots in twenty twenty two is that the housing market 0:19:56.920 --> 0:19:59.439 was pretty resilient. There are lots of people out there 0:19:59.480 --> 0:20:03.360 who thought that mortgage rates going up spectacularly meant that 0:20:03.440 --> 0:20:07.760 housing prices would inevitably have to go down. But as 0:20:07.840 --> 0:20:11.120 our guest Jim Egan, a strategist at Morgan Stanley, has 0:20:11.160 --> 0:20:15.600 pointed out repeatedly, that is not necessarily the case. Instead, 0:20:15.640 --> 0:20:19.600 we've seen, you know, basically a freeze in the market. 0:20:20.320 --> 0:20:25.119 Jim in general is full of interesting facts and figures 0:20:25.200 --> 0:20:28.240 and stats about US real estate, and whenever he comes 0:20:28.240 --> 0:20:30.040 on the show, he sort of throws out all these 0:20:30.080 --> 0:20:33.679 really interesting numbers. One of the most interesting numbers he 0:20:33.800 --> 0:20:36.639 told us this year has to do with the number 0:20:36.680 --> 0:20:39.360 of houses currently owned by baby boomers. 0:20:39.640 --> 0:20:42.560 I think the reason that we haven't been as focused 0:20:42.600 --> 0:20:47.240 on older age cohorts as an industry is because historically 0:20:47.320 --> 0:20:51.080 they just haven't been that large. The boomer generation moving 0:20:51.119 --> 0:20:55.359 into this age cohort is really driving kind of differentiated 0:20:55.640 --> 0:20:58.600 housing dynamics. If we look at the percentage of homes 0:20:58.760 --> 0:21:01.119