WEBVTT - Why the CRE Urban Doom Loop May Still Be Coming 0:00:03.120 --> 0:00:12.960 Bloomberg Audio Studios, Podcasts, Radio News. 0:00:20.200 --> 0:00:23.919 Hello and welcome to another episode of the Odd Lots Podcast. 0:00:24.000 --> 0:00:26.200 I'm Joe Wisenthal and I'm Tracy Alloway. 0:00:26.440 --> 0:00:29.240 Tracy, So, you know, we had that conversation the other 0:00:29.360 --> 0:00:32.800 day with rich Hill Cohenan Steers, and you sort of 0:00:32.840 --> 0:00:37.000 put like a maybe not too gloomy gloss on. 0:00:37.040 --> 0:00:41.360 The commerci not too gloomy gloss, not too gloomy gloss. 0:00:41.920 --> 0:00:44.519 It's a good one, uh like not great, but like 0:00:44.720 --> 0:00:48.479 maybe like not terrible. That like price discovery is happening. 0:00:48.560 --> 0:00:52.960 It's not great, but it's salvageable. There's still room for 0:00:53.040 --> 0:00:55.720 extending and pretending it's not the end of the world. Like, 0:00:55.880 --> 0:00:57.400 you know, not great, but not terrible. 0:00:57.520 --> 0:00:59.520 Yeah, And I think to some extent, we've seen that 0:01:00.200 --> 0:01:03.440 out in markets in recent months. Right, So there were 0:01:03.480 --> 0:01:07.679 all these stories about the looming maturity wall. Yeah, a 0:01:07.680 --> 0:01:10.039 lot of those loans, a lot of those bonds have 0:01:10.120 --> 0:01:14.320 been refinanced, a lot of companies are surviving, a lot 0:01:14.319 --> 0:01:17.720 of building owners or real estate developers seem to be 0:01:17.800 --> 0:01:20.960 surviving under the new conditions. But I guess the wild 0:01:21.040 --> 0:01:23.080 card in a lot of this is still what happens 0:01:23.080 --> 0:01:23.919 with interest rates. 0:01:24.319 --> 0:01:26.600 Here's what I don't get though, Like, at least when 0:01:26.600 --> 0:01:29.160 we're talking about office and when we're talking about office 0:01:29.200 --> 0:01:32.960 real estate in big cities, the vacancy rates keep going up. 0:01:33.160 --> 0:01:35.640 And I sort of thought that would stop, because you know, 0:01:35.760 --> 0:01:37.959 especially in the middle of last year, you saw a 0:01:38.040 --> 0:01:41.720 number of pushes where companies like, no, we're serious, it's 0:01:41.800 --> 0:01:44.520 return to the office time, guys, And so I was like, oh, okay, 0:01:44.560 --> 0:01:47.000 like that was it, this was the turning point. And 0:01:47.120 --> 0:01:49.640 yet I think by like at least top line metrics, 0:01:49.640 --> 0:01:51.480 if you just sort of look at offices and the 0:01:51.520 --> 0:01:54.160 empty ones, things continue to deteriorate. 0:01:54.320 --> 0:01:57.200 Office buildings are still empty in places like New York 0:01:57.240 --> 0:01:59.720 and San Francisco. This is very true, but I think 0:01:59.800 --> 0:02:03.200 really ate, like people still want to live here residential 0:02:03.240 --> 0:02:06.360 real estate. I mean, I think those vacancies are pretty low. 0:02:06.440 --> 0:02:09.680 So there is this like there's this tension where people 0:02:09.840 --> 0:02:12.000 still want to come to the city, it feels like, 0:02:12.080 --> 0:02:14.359 or at least move here, but they don't want to 0:02:14.400 --> 0:02:17.000 go into the office, which fair enough I sympathize. 0:02:17.120 --> 0:02:21.200 So just a full disclosure or you know, my own 0:02:21.400 --> 0:02:24.200 stake in this story, which is that last year I 0:02:24.280 --> 0:02:28.000 bought an apartment in Manhattan. So I am really invested 0:02:28.200 --> 0:02:31.400 in the idea that Manhattan continues to be a thriving, 0:02:32.040 --> 0:02:37.320 going concern with people on the streets, looking around, moving about. 0:02:37.440 --> 0:02:39.120 I feel like that's you know, it's good. It feels 0:02:39.120 --> 0:02:41.440 good for safety, things like that. I really need this 0:02:41.480 --> 0:02:42.480 whole thing to hang together. 0:02:42.600 --> 0:02:46.160 And I'm on the opposite side of this trade, I 0:02:46.200 --> 0:02:49.640 think where I have no Manhattan ownership. I rent, I 0:02:49.639 --> 0:02:52.200 would like the rent to go down actually, and I 0:02:52.240 --> 0:02:55.280 have a house out in the country. So yeah, we'll. 0:02:54.960 --> 0:02:58.040 Debate between the two of us. Tracy, we're perfectly. 0:02:57.760 --> 0:02:58.440 Well well hedged. 0:02:58.560 --> 0:03:01.360 Yeah, that's right, we're perfect He well. Anyway, so we 0:03:01.440 --> 0:03:04.720 had that conversation with rich Hill last week and he 0:03:04.880 --> 0:03:07.760 mentioned he said, oh, there's this NYU professor who was 0:03:07.840 --> 0:03:11.919 one super gloomy about the urban doom loop real estate apocalypse, 0:03:12.080 --> 0:03:15.160 and he even he's changed his tone. And then when 0:03:15.160 --> 0:03:17.480 he said that, I thought two things. It's like, hey, 0:03:17.760 --> 0:03:20.880 I know that guy. Yeah, he's even been to some 0:03:20.919 --> 0:03:23.000 odd logeed trivia nights. And b I didn't realize he 0:03:23.000 --> 0:03:25.240 had changed his tone. I didn't even know if that's true. 0:03:25.400 --> 0:03:27.960 Got stateated on air. I hope it's true, because I 0:03:28.040 --> 0:03:30.880 want things to be factual on the podcast. So it's 0:03:30.919 --> 0:03:33.480 like if we should actually we should talk to we 0:03:33.480 --> 0:03:35.080 should talk to that NYU professor. 0:03:35.200 --> 0:03:37.880 I like that our fact checks have become sources of content. 0:03:38.000 --> 0:03:41.240 Now it's just another episode to see if what someone 0:03:41.320 --> 0:03:42.880 already said is actually correct. 0:03:42.880 --> 0:03:44.760 We could have just done a fact check, or we 0:03:44.880 --> 0:03:47.080 just put it out there and then if it's wrong 0:03:47.200 --> 0:03:49.320 then we get it, we get it debunked on a 0:03:49.320 --> 0:03:50.000 future episode. 0:03:50.040 --> 0:03:51.840 All right, let's find it out if it's wrong or not. 0:03:52.000 --> 0:03:54.520 Well, I'm very excited. We're going to be speaking with 0:03:54.840 --> 0:03:58.000 Arbid Gupta. He's an associate professor of Finance at NYU 0:03:58.080 --> 0:04:01.040 Stern and back in twenty twenty two, he was the 0:04:01.040 --> 0:04:03.840 co author of a paper work from Home and the Office, 0:04:03.840 --> 0:04:06.760 Real Estate Apocalypse. Of course, there's all this fear of 0:04:06.840 --> 0:04:09.000 doom loops. People don't go into the office. Then the 0:04:09.040 --> 0:04:12.840 local businesses that depended on that foot traffic, like Delhi's 0:04:12.880 --> 0:04:15.120 and salad bars and restaurants go out of business, and 0:04:15.120 --> 0:04:16.920 then people don't like being in the city even more, 0:04:16.920 --> 0:04:19.120 and then they move out to the middle of nowhere 0:04:19.160 --> 0:04:22.440 like you. And then suddenly the whole thing falls apart, Arbet, 0:04:22.640 --> 0:04:25.080 thank you so much for coming in, Thanks so much 0:04:25.080 --> 0:04:27.440 for having me. Let's just start with like the basic 0:04:27.560 --> 0:04:31.359 fact check question, are you as gloomy or do you 0:04:31.440 --> 0:04:34.360 have the same fears of an office real estate apocalypse 0:04:34.600 --> 0:04:36.280 as you did in late twenty twenty two. 0:04:36.480 --> 0:04:39.880 Great, So, taking a step back, my co author Teams 0:04:39.880 --> 0:04:42.320 and I, so that includes stan One Neiberg who was 0:04:42.360 --> 0:04:44.520 at Columbia, as well as RNDA Methol who was at 0:04:44.600 --> 0:04:48.400 unc first began with a research paper that was looking 0:04:48.440 --> 0:04:52.360 at the urban flight and residential real estate. So we 0:04:52.360 --> 0:04:55.440 were comparing the price of real estate in the center 0:04:55.480 --> 0:04:58.360 of cities against the price of residential real estate in 0:04:58.400 --> 0:05:01.560 the suburbs. And we found is that over the course 0:05:01.600 --> 0:05:04.200 of the pandemic, the price of suburban real estate, so 0:05:04.320 --> 0:05:06.720 places like where Tracy lives have gone up from. 0:05:06.640 --> 0:05:10.720 Maga's really like ex surban but yes, keep going. 0:05:10.520 --> 0:05:13.840 No, it's really those far far exurban places, places that 0:05:13.880 --> 0:05:16.320 weren't even really considered commutable, that actually went up in 0:05:16.400 --> 0:05:20.240 value the most relative to real estate in the center 0:05:20.240 --> 0:05:22.800 of the city, places like where Joe lives, right, And 0:05:22.920 --> 0:05:26.280 so we find that that spread is corresponding to a 0:05:26.600 --> 0:05:29.760 rent gradient or a price gradient really narrowed, and in fact, 0:05:29.800 --> 0:05:32.720 that narrowing has continued even through twenty twenty three. So 0:05:32.880 --> 0:05:36.600 urban real estate continues to lose value relative to suburban 0:05:36.640 --> 0:05:40.200 and far exurban residential real estate. We find that that 0:05:40.240 --> 0:05:42.279 pattern is really driven by remote work. So it's people 0:05:42.279 --> 0:05:44.760 that are willing to move further and further away from 0:05:44.760 --> 0:05:47.280 the city and are less willing to pay for urban 0:05:47.320 --> 0:05:50.880 amenities and proximity to urban work locations. That's kind of 0:05:50.960 --> 0:05:54.160 driving this spatial arbitrage across markets. 0:05:54.480 --> 0:05:57.640 How do you square that spatial arbitrage idea or that 0:05:57.720 --> 0:06:04.000 price discrepancy urban versus non urban prices with the sense 0:06:04.160 --> 0:06:07.680 that I mean, it certainly feels reading the headlines, and again, 0:06:07.800 --> 0:06:09.760 Joe and I might be slightly biased here because we 0:06:09.800 --> 0:06:13.839 work in financial journalism adjacent to the financial industry, but 0:06:13.920 --> 0:06:16.320 it feels like there is a drive to get people 0:06:16.360 --> 0:06:17.680 back into the office. 0:06:17.880 --> 0:06:20.839 Absolutely, and I think this really varies across cities and 0:06:20.839 --> 0:06:24.920 across industries. Right, so when you look at the entire country, 0:06:25.040 --> 0:06:28.400 there's really no good indication that people are more likely 0:06:28.800 --> 0:06:31.719 to come into the office. Whether you're looking at surveys 0:06:31.760 --> 0:06:33.520 that kind of ask people, how often are you coming 0:06:33.560 --> 0:06:35.800 to the office or not, or surveys that ask firms 0:06:35.839 --> 0:06:38.080 what are your policies or not. But one trend that 0:06:38.240 --> 0:06:40.400 is pretty noticeable is it's a lot of the largest 0:06:40.400 --> 0:06:42.640 companies that kind of make up the headlines, firms like 0:06:42.680 --> 0:06:45.679 Goldman Sacks, they're very vocal about their back to office plans. 0:06:46.200 --> 0:06:49.360 And you see across some industries, particularly industries like finance, 0:06:49.520 --> 0:06:51.760 they are a little bit more inclined to get workers 0:06:51.760 --> 0:06:53.040 into the office. So it's really kind of hard to 0:06:53.080 --> 0:06:55.679 see a nationwide trend, but it is there in certain 0:06:55.720 --> 0:06:56.640 industries or firms. 0:06:56.920 --> 0:07:01.760 So is the doom looping, like, is it spiraling or 0:07:01.800 --> 0:07:03.640 has anything arrested it? 0:07:04.320 --> 0:07:08.039 Right? So we looked at this aspect of urban flight, 0:07:08.120 --> 0:07:11.200 and so across many cities like New York or San Francisco, 0:07:11.280 --> 0:07:13.400 you see a population loss of about six to eight 0:07:13.440 --> 0:07:16.000 percent that happened over the course of the pandemic, and 0:07:16.040 --> 0:07:19.360 this population loss has sort of stabilized. So San Francisco 0:07:19.520 --> 0:07:22.000 gained a small amount of population last year. New York 0:07:22.200 --> 0:07:24.840 continued to lose population, but at a smaller rate than 0:07:24.920 --> 0:07:28.880 previous years, and that kind of motivated us to look 0:07:28.920 --> 0:07:31.640 into what are the implications for commercial office buildings and 0:07:31.720 --> 0:07:34.160 this concept of the of the doom loop. So in 0:07:34.200 --> 0:07:35.920 our paper that came out a couple of years ago, 0:07:36.280 --> 0:07:39.440 we estimated that New York City office real estate would 0:07:39.480 --> 0:07:42.560 be down in value about forty to fifty percent. And 0:07:42.760 --> 0:07:46.360 this can lead to two possible spillovers, right. So one 0:07:46.680 --> 0:07:49.520 is the impact on financial institutions and banks in particular 0:07:49.600 --> 0:07:51.840 that are holding a lot of the debt associated with 0:07:51.840 --> 0:07:54.280 office buildings. So that's a financial doom loop risk. 0:07:54.400 --> 0:07:54.600 Right. 0:07:54.880 --> 0:07:58.600 So as the value of these properties declines, loans attached 0:07:58.680 --> 0:08:01.080 these properties might enter into full and we're seeing default 0:08:01.120 --> 0:08:03.960 rates now about six to seven percent. That might trigger 0:08:04.640 --> 0:08:08.480 foreclosures to stress sales that then amplify back and feed 0:08:08.480 --> 0:08:11.040 into further real estate price to clients. We're seeing the 0:08:11.080 --> 0:08:14.680 beginnings of this play out, but modification efforts have sort 0:08:14.680 --> 0:08:17.360 of stemmed this tide for now. The other externality or 0:08:17.360 --> 0:08:19.880 spillover effect comes onto cities, right, And so that's this 0:08:20.040 --> 0:08:23.120 urban doom blup idea that you're going to see a 0:08:23.160 --> 0:08:27.000 cycle driven by remote work leading to office vacancy losses, 0:08:27.600 --> 0:08:30.680 loss and property value that then hits city budgets. City 0:08:30.720 --> 0:08:33.280 governments therefore lose money and are forced because of balanced 0:08:33.280 --> 0:08:37.120 budget requirements to either raised taxes or cut services, and 0:08:37.160 --> 0:08:38.839 people don't like either of those, and so they might 0:08:38.920 --> 0:08:42.600 respond by leaving the city in greater numbers, which might 0:08:42.640 --> 0:08:46.560 then further amplify those losses. And so we're seeing, i think, 0:08:46.679 --> 0:08:49.240 is sort of the first wave of those events happen 0:08:49.280 --> 0:08:52.880 with the population loss, the loss and value for commercial 0:08:52.880 --> 0:08:54.800 real estate. And it's really now kind of in the 0:08:54.840 --> 0:08:57.800 hands of policymakers to kind of decide how they choose 0:08:57.800 --> 0:09:00.920 to respond to those treads, right, whether they're going to 0:09:01.200 --> 0:09:05.920 respond to these losses by trying to kind of raise taxes, 0:09:05.960 --> 0:09:08.360 cut spending, or trying to improve the quality of life 0:09:08.559 --> 0:09:09.800 and amenities in urbine areas. 0:09:10.240 --> 0:09:13.720 So you're the forty percent estimate. So the idea that 0:09:13.800 --> 0:09:17.280 long run office valuations are forty percent below their pre 0:09:17.400 --> 0:09:21.120 pandemic levels per your paper, that was kind of assuming 0:09:21.280 --> 0:09:24.840 that everything pretty much stays the same. Is that right? 0:09:25.240 --> 0:09:28.560 So we are trying to figure out how persistent remote 0:09:28.559 --> 0:09:30.679 work is going to be, Right, So we're acknowledging the 0:09:30.720 --> 0:09:34.880 possibility that these firms might be successful in bringing people 0:09:35.080 --> 0:09:37.560 back into the office, and we're trying to estimate how 0:09:37.760 --> 0:09:41.160 likely is that going to happen. We ultimately back that 0:09:41.280 --> 0:09:44.920 number out by looking at publicly traded stock prices. So 0:09:45.040 --> 0:09:47.800 the idea is we sort of solve acid pricing model 0:09:48.040 --> 0:09:51.000 that has a key parameter being how likely are firms 0:09:51.400 --> 0:09:53.560 to be successful in bringing people back to the office. 0:09:53.559 --> 0:09:55.840 And basically the only way we can kind of match 0:09:56.200 --> 0:09:59.640 publicly traded read prices so stocks like Brenado, essel Green 0:10:00.280 --> 0:10:03.440 is by getting a parameter an estimate for how persistent 0:10:03.480 --> 0:10:04.920 remote work is likely to be. It's going to be 0:10:05.000 --> 0:10:08.400 pretty high. So we're basically estimating how likely is it 0:10:08.640 --> 0:10:11.040 that we're going to stay in this remote work equilibrium, 0:10:11.040 --> 0:10:13.640 and we sort of estimate that it's a pretty high likelihood. 0:10:13.840 --> 0:10:16.560 So this world sort of seems to be persistent for now. 0:10:16.920 --> 0:10:20.120 Yeah, it is striking. So prior to the pandemic, shares 0:10:20.160 --> 0:10:23.240 of Vernado were about seventy dollars a year. In the 0:10:23.280 --> 0:10:25.880 middle of twenty twenty three, they hit as low as 0:10:25.880 --> 0:10:29.280 twelve seventy nine and they've rebounded, but they're only back 0:10:29.320 --> 0:10:32.160 up to just under thirty dollars, so still about basically 0:10:32.200 --> 0:10:34.280 cut in half versus pre pandemic levels, and I think 0:10:34.360 --> 0:10:35.920 sl Green looks pretty similar. 0:10:36.040 --> 0:10:38.280 Yeah, and the other major pricing indicator to look at 0:10:38.320 --> 0:10:41.960 is the CMBX series. Right. So, back in the financial crisis, 0:10:42.160 --> 0:10:45.000 a lot of short traders were looking at the ABX series, 0:10:45.040 --> 0:10:48.120 which was tracking credit to fault swaps on the price 0:10:48.120 --> 0:10:51.160 of non agency mortgage backed securities. So the CMBX index 0:10:51.280 --> 0:10:55.800 similarly tracks the value of CMBs deals, which are backed 0:10:55.840 --> 0:10:59.160 by bundles of large numbers of commercial real estate mortgages, 0:10:59.559 --> 0:11:02.400 and these bundles vary in how much office they have. 0:11:02.880 --> 0:11:04.880 But what we're seeing is a value loss in the 0:11:04.960 --> 0:11:07.720 CMBX index, which might vary from between fifteen and twenty 0:11:07.800 --> 0:11:11.719 five percent for a triple b CNBX references in DEX. 0:11:11.800 --> 0:11:15.160 So that basically means that market participants expect there to 0:11:15.200 --> 0:11:19.120 be some value loss in these depths accuritizations backed by 0:11:19.120 --> 0:11:19.960 commercial real estate. 0:11:36.280 --> 0:11:39.160 Since you mentioned the ABX, and now I have all 0:11:39.200 --> 0:11:42.880 these subprime memories flooding back. But part of the problem there, 0:11:42.960 --> 0:11:45.480 or part of the reason the losses were a lot 0:11:45.559 --> 0:11:48.719 higher than a lot of people expected, was because we 0:11:48.840 --> 0:11:52.959 estimated the correlation wrong. Right, mortgages when they started going bad, 0:11:53.120 --> 0:11:55.800 it wasn't just isolated incidents. It ended up being across 0:11:55.840 --> 0:11:58.360 the country. What do you see in terms of correlation 0:11:58.720 --> 0:12:02.440 or relationship when it comes to vacant office buildings. Do 0:12:02.480 --> 0:12:05.960 you see like if one office building doesn't have a 0:12:05.960 --> 0:12:08.720 lot of business inside it or a lot of renters, 0:12:08.880 --> 0:12:10.720 does that impact the ones around it? 0:12:11.000 --> 0:12:14.080 So there probably is this correlation risk within office and 0:12:14.120 --> 0:12:18.120 maybe other adjacent asset classes like urban retail. And the 0:12:18.160 --> 0:12:21.679 reason for that is if an office building is vacant, 0:12:21.720 --> 0:12:23.560 if people aren't going there, well, that just makes it 0:12:23.559 --> 0:12:26.640 a less attractive destination, even for other people within the 0:12:26.640 --> 0:12:29.480 same office district. So a good example of this might 0:12:29.520 --> 0:12:33.120 be DC. So DC actually has a really high remote 0:12:33.160 --> 0:12:35.439 working rate, in part because a lot of federal government 0:12:35.440 --> 0:12:38.800 employees have fairly generous remote working policies, and so that 0:12:38.880 --> 0:12:41.079 means that a lot of different office buildings in the 0:12:41.160 --> 0:12:45.079 DC market are all experiencing high vacancy at the same time. 0:12:45.480 --> 0:12:47.880 That does have some spill or effects to other corners 0:12:47.880 --> 0:12:50.440 of commercial real estate. So if I'm looking at retail 0:12:50.600 --> 0:12:53.760 in DC or in some markets like San Francisco, even 0:12:53.840 --> 0:12:57.520 hospitality hotels or impacted as well, but it is confined 0:12:57.559 --> 0:13:00.679 more to those specific asset classes and doesn't necessarily spill 0:13:00.720 --> 0:13:03.000 over to all of commercial real estate, which, as we 0:13:03.080 --> 0:13:05.640 both know, is a very large, heterogenious universe, a lot 0:13:05.679 --> 0:13:06.520 of different asset tymes. 0:13:06.559 --> 0:13:08.959 I remember we used to talk sometimes like on TV 0:13:09.160 --> 0:13:11.400 to Emerging markets manager and it's like, oh, it's very 0:13:11.440 --> 0:13:14.200 important to remember not all em is a monolith. And 0:13:14.240 --> 0:13:17.840 now I feel like all CIRE discussions similar thing. You 0:13:17.920 --> 0:13:20.480 must get in there that CIRI is not a monolith. 0:13:20.520 --> 0:13:24.679 It includes many different categories. The key maybe dichotomy or 0:13:24.760 --> 0:13:26.920 question as you sort of set it out, is do 0:13:27.040 --> 0:13:33.920 cities respond to population flight by raising taxes which might 0:13:33.960 --> 0:13:36.440 accelerate population flight, or cutting spending which might do the 0:13:36.440 --> 0:13:39.559 same thing, or do they find some way of actually 0:13:39.600 --> 0:13:43.000 reversing that trend and making people not want to move out? 0:13:43.040 --> 0:13:44.840 Like what are they doing so far? 0:13:45.320 --> 0:13:47.040 So I think the important thing to keep in mind 0:13:47.160 --> 0:13:49.880 is the really long lags built into all of this, Right, 0:13:50.080 --> 0:13:53.120 So the office leases are really long term in nature, 0:13:53.240 --> 0:13:56.400 and so even to this point, many firms haven't had 0:13:56.440 --> 0:14:00.000 to make an active space decision yet because they're still 0:14:00.080 --> 0:14:02.600 inherited at least from before the pandemic. Then you have 0:14:02.760 --> 0:14:05.719 the mortgages on these assets that are also really long 0:14:05.800 --> 0:14:08.320 term in nature, and so you haven't had to hit 0:14:08.360 --> 0:14:11.520 a refinancing point yet. For these owners. And then finally 0:14:11.520 --> 0:14:14.079 you have the property tax assessment cycle, which is also 0:14:14.400 --> 0:14:17.000 really long, so it takes a really long time for 0:14:17.080 --> 0:14:20.680 cities to necessarily recognize a loss in property value in 0:14:20.720 --> 0:14:22.720 their tax re seats. Right, So a lot of cities 0:14:22.800 --> 0:14:26.240 haven't yet really faced this fiscal reckoning yet. It's really 0:14:26.240 --> 0:14:27.760 more of the long term that they're going to be 0:14:27.800 --> 0:14:31.760 potentially facing lower property tax re seats coming from lower 0:14:31.800 --> 0:14:34.920 property tax revenue from these commercial office buildings, coming from 0:14:35.040 --> 0:14:37.560 lower income taxes from people that have left, as well 0:14:37.600 --> 0:14:40.720 as lower sales taxes from less spending that's happening in 0:14:40.840 --> 0:14:43.960 urban districts. So most cities haven't really had to face 0:14:43.960 --> 0:14:46.440 the impacts of this yet. They've also benefited from one 0:14:46.480 --> 0:14:49.720 time federal relief funds. But in the future, a lot 0:14:49.720 --> 0:14:53.400 of cities are projecting future deficits, and part of that 0:14:53.440 --> 0:14:56.320 just reflects conservative accounting on the part of city governments, 0:14:56.560 --> 0:15:00.480 so they're sort of accounting for the possible ability that 0:15:00.520 --> 0:15:02.960 revenues in the future may just kind of come in slower. 0:15:03.000 --> 0:15:06.560 So it's not yet clear whether these deficits will materialize 0:15:06.640 --> 0:15:08.440 in the future. But what we can say is when 0:15:08.480 --> 0:15:11.160 we look back in the past, the conservative forecasts on 0:15:11.200 --> 0:15:14.480 revenues wound up being exceeded because cities actually wound up 0:15:14.480 --> 0:15:17.640 getting a lot more money than they expected in property taxes. 0:15:17.680 --> 0:15:20.640 So a lot of these core assets, like office buildings, 0:15:20.680 --> 0:15:23.600 we're really providing cities with a lot of additional revenue 0:15:23.600 --> 0:15:25.560 in the past ten to fifteen years, and so they 0:15:25.560 --> 0:15:27.080 may not be in a position to get the same 0:15:27.120 --> 0:15:29.640 amount of revenue from those office buildings, which then force 0:15:29.680 --> 0:15:31.760 the cities to do a variety of different things to 0:15:31.800 --> 0:15:34.480 try to make sure that they remain attractive, vibrant places 0:15:34.480 --> 0:15:36.720 to be. So one big response cities are trying to 0:15:36.720 --> 0:15:38.720 do is conversions. Right, so if you can take this 0:15:38.920 --> 0:15:42.480 structurally obsolescent, you know, stranded asset office real estate class 0:15:42.600 --> 0:15:46.520 and turn it into housing or some other use case. Housing, 0:15:46.560 --> 0:15:48.560 of course is great because everyone wants more housing in 0:15:48.640 --> 0:15:51.280 dense urban areas. That is a great way to kind 0:15:51.280 --> 0:15:53.680 of fill up the city, fill up the subway systems. 0:15:53.720 --> 0:15:57.040 Those subway systems are also kind of experiencing declines and 0:15:57.120 --> 0:15:59.000 ridership as well, and so that's something a lot of 0:15:59.040 --> 0:16:02.200 cities are looking actively at. In addition to just converting 0:16:02.280 --> 0:16:05.360 additional office space or just changing regulation around housing. More broadly, 0:16:05.480 --> 0:16:07.280 so we can build more housing in cities. 0:16:07.640 --> 0:16:10.280 This reminds me actually, one thing that often comes up 0:16:10.360 --> 0:16:14.640 in these urban doom loop discussions is the example of 0:16:14.680 --> 0:16:17.760 New York in the nineteen seventies, nineteen eighties, or even 0:16:17.840 --> 0:16:21.480 after two thousand and one and nine to eleven, and 0:16:21.600 --> 0:16:24.080 the idea that well, there there was a sort of 0:16:24.120 --> 0:16:27.520 discussion about New York is in a long run decline 0:16:27.560 --> 0:16:29.520 and it's going to be impossible for it to get out, 0:16:29.560 --> 0:16:32.760 and yet it did in one way or another. How 0:16:32.800 --> 0:16:34.600 did it manage to achieve that? And what does that 0:16:34.640 --> 0:16:38.160 say about the current policy trajectory. 0:16:38.600 --> 0:16:41.000 So when we coined that term in our paper, we 0:16:41.080 --> 0:16:44.240 really weren't thinking about this the industrialization shock which hit 0:16:44.320 --> 0:16:46.520 a lot of rust belt cities, right and so you 0:16:46.520 --> 0:16:49.280 saw cities like Detroit or Saint Louis Louis about fifty 0:16:49.360 --> 0:16:52.160 or sixty percent of their population over that time as 0:16:52.200 --> 0:16:54.920 they kind of lost that center industry which was holding 0:16:55.000 --> 0:16:58.400 up their entire ecosystem. For cities like New York, it 0:16:58.560 --> 0:17:01.120 also was a pretty bad shock. So the city lost 0:17:01.160 --> 0:17:04.720 something like a million manufacturing jobs that were previously located 0:17:04.800 --> 0:17:06.920 right in the heart of the city. So we had 0:17:06.920 --> 0:17:10.400 this big surplus of real estate associated with these industrial 0:17:10.480 --> 0:17:14.200 logistics uses that had to get redeployed towards other things. 0:17:14.359 --> 0:17:16.680 And ultimately we found here in York that you could 0:17:16.800 --> 0:17:20.480 take these buildings and convert them to retail housing and 0:17:20.560 --> 0:17:22.200 support a lot of office buildings. So a lot of 0:17:22.280 --> 0:17:24.960 white collar work came to New York in the aftermath 0:17:25.000 --> 0:17:27.639 of that deindustrialization period, so some cities were able to 0:17:28.040 --> 0:17:30.879 ultimately prove to be more resilient. We also see across 0:17:30.920 --> 0:17:33.119 cities that meds and eds were a really big factor. 0:17:33.160 --> 0:17:36.320 So having hospitals and educational institutions were a great way 0:17:36.320 --> 0:17:39.120 for economies to kind of pivot and create new job 0:17:39.200 --> 0:17:42.160 centers of growth in order to take over the previous 0:17:42.200 --> 0:17:44.280 blue collar work that would have been going on in cities. 0:17:44.400 --> 0:17:46.720 And so some of those cities, again, particularly like New York, 0:17:46.720 --> 0:17:49.560 were able to kind of redeploy and change their economic 0:17:49.640 --> 0:17:50.640 environment in response. 0:17:50.920 --> 0:17:54.160 We are recording this merch twenty fifth, twenty twenty four. 0:17:54.320 --> 0:17:57.760 So on March fifth, twenty twenty four, how are you feeling. 0:17:58.040 --> 0:18:00.600 Let's start with New York specifically, because that's all care about. No, 0:18:00.640 --> 0:18:02.920 it's not all I care about, just ninety percent. How 0:18:02.920 --> 0:18:04.520 are you feeling about New York right now. 0:18:04.760 --> 0:18:06.080 So I think New York has a lot of great 0:18:06.119 --> 0:18:09.159 advantages going for it. So it begins with the diversified 0:18:09.160 --> 0:18:12.119 industrial base, right so, in comparison to a lot of 0:18:12.119 --> 0:18:14.760 these West Coast cities, in comparison to city like San 0:18:14.760 --> 0:18:17.800 Francisco right now has something like a thirty seven percent 0:18:18.359 --> 0:18:22.639 office vacancy rate. At those rates, if you had the 0:18:22.920 --> 0:18:26.680 fastest office absorption in history, you would still need seven 0:18:26.760 --> 0:18:29.800 or eight years just to fill the existing vacant office space. 0:18:30.320 --> 0:18:32.959 If you are filling San Francisco office at the average 0:18:33.280 --> 0:18:35.600 rate of absorption over the last twenty years, you need 0:18:35.600 --> 0:18:38.520 something like fifteen or more years to actually fill all 0:18:38.560 --> 0:18:40.920 of that office space. So there's just a huge vacancy 0:18:40.960 --> 0:18:44.040 problem in a lot of these West Coast tech center 0:18:44.200 --> 0:18:47.280 centity cities. In comparison, New York just has a broad 0:18:47.320 --> 0:18:50.760 diversity of different industrial uses, and you have a lot 0:18:50.760 --> 0:18:53.359 of firms like big law or financial firms that do 0:18:53.440 --> 0:18:56.440 seem to be more able to get workers into the office. 0:18:56.560 --> 0:18:59.080 In addition, you have a lot of great consumption amenities, 0:18:59.240 --> 0:19:01.160 so people love being in New York for all sorts 0:19:01.160 --> 0:19:03.080 of different reasons. That's going to mean that New York 0:19:03.359 --> 0:19:05.960 is in the position to reinvent itself as more of 0:19:05.960 --> 0:19:09.479 a consumption city rather than a production city. And then finally, 0:19:09.480 --> 0:19:12.560 there's another great buffer that New York City has, which is, 0:19:12.560 --> 0:19:14.640 if you're looking at office rents that are let's say 0:19:14.800 --> 0:19:17.520 seventy dollars or eighty dollars a square foot, you have 0:19:17.640 --> 0:19:20.800 the space to cut that rent down and get to 0:19:20.840 --> 0:19:22.959 a point where you're able to find some other tenant 0:19:23.000 --> 0:19:25.520 willing to come into that space. Now, office owners, for 0:19:25.600 --> 0:19:28.080 variety reasons we can get into, are reluctant to lower 0:19:28.119 --> 0:19:30.919 the rent to that point. But there is space to 0:19:30.960 --> 0:19:33.119 lower the rent and still be able to operate that 0:19:33.240 --> 0:19:36.840 building financially. In comparison, you have a lot of other cities, 0:19:36.880 --> 0:19:40.040 for example, some other Roust Belt cities, where there's not 0:19:40.040 --> 0:19:42.240 necessarily that same level of space to cut the office 0:19:42.240 --> 0:19:45.159 rent without really eating into the ability to operate that 0:19:45.160 --> 0:19:46.080 building successfully. 0:19:46.160 --> 0:19:48.639 This was going to be exactly my next question. So 0:19:48.760 --> 0:19:52.600 what is the catalyst for office owners or building owners 0:19:52.640 --> 0:19:56.320 to finally reduce rents, because presumably that's when you get 0:19:56.359 --> 0:20:00.200 the sort of healing process, the creative destruction. I guess 0:20:00.359 --> 0:20:03.639 that allows new types of businesses to come into the 0:20:03.680 --> 0:20:07.040 city and maybe start redefining some of these urban areas. 0:20:07.760 --> 0:20:09.920 I think in many cases it's really going to require 0:20:09.920 --> 0:20:12.880