WEBVTT - Hurricanes, Housing, and Tipping 0:00:01.280 --> 0:00:05.280 You're listening to the Bloomberg Opinion podcast counts Saturdays at 0:00:05.280 --> 0:00:08.400 one and seven pm Eastern on Bloomberg dot Com, the 0:00:08.480 --> 0:00:11.600 iHeartRadio app and the Bloomberg Business App, or listen on 0:00:11.680 --> 0:00:13.760 demand wherever you get your podcasts. 0:00:15.560 --> 0:00:19.239 Welcome to Bloomberg Opinion. I'm Amy Morris. This week we 0:00:19.239 --> 0:00:22.720 look at manufactured homes, how to reinforce them, protect them, 0:00:23.120 --> 0:00:26.400 and help residents who live in them. We'll also look 0:00:26.440 --> 0:00:29.479 at how a new trend in tipping might actually be 0:00:29.600 --> 0:00:32.920 hurting those who need those tips the most, and later 0:00:33.000 --> 0:00:35.600 a look at the alcohol industry, which is facing a 0:00:35.680 --> 0:00:40.400 real threat from competition and low to know alcohol trends. 0:00:41.040 --> 0:00:44.120 Let's begin, though, with a look at insurance, especially as 0:00:44.159 --> 0:00:47.800 we are seeing more severe weather, which is prompting more 0:00:47.880 --> 0:00:51.880 insurance companies to pull out of high risk areas. Experts 0:00:51.880 --> 0:00:55.680 are warning of an insurance crisis unfolding as natural disasters 0:00:55.720 --> 0:01:00.200 get more expensive and insurance companies bail Benjamin keys Is 0:01:00.200 --> 0:01:03.400 with the University of Pennsylvania Wharton School of Business. 0:01:03.680 --> 0:01:09.319 We think of Florida, Arizona, Louisiana as being popular retirement destinations, 0:01:09.360 --> 0:01:12.280 and those destinations just got a bit costlier to move 0:01:12.319 --> 0:01:14.280 to because of rising insurance costs. 0:01:14.400 --> 0:01:17.160 Well, now it's probably a good time for property owners 0:01:17.200 --> 0:01:20.880 to check those insurance policies and buckle up for dramatically 0:01:20.959 --> 0:01:26.200 higher costs. You can blame climate, macroeconomic pressures, political factors 0:01:26.200 --> 0:01:29.360 that have battered the insurance industry in recent years. Let's 0:01:29.360 --> 0:01:32.800 talk about it now. Bloomberg opinion columnist David Fickling joins me. 0:01:33.000 --> 0:01:36.319 David covers Energy and Commodities. David tell us what we 0:01:36.440 --> 0:01:40.280 might find as we do start to review our insurance policies. 0:01:40.800 --> 0:01:45.479 Yeah, well, it's looking a pretty rough year for anyone 0:01:45.520 --> 0:01:51.760 who's got an insurance policy. Beasley PLC one of the 0:01:51.880 --> 0:01:53.880 UK based insurance but have a lot of coverage in 0:01:53.880 --> 0:01:56.400 the US. They said recently that propertian is in the 0:01:56.520 --> 0:02:02.960 US are already seeing annual rate increases averaging seventeen percent. So, 0:02:03.360 --> 0:02:06.840 you know, a year when we're already seeing pretty high 0:02:07.720 --> 0:02:12.800 inflationary costs, insurance is going up faster than the fastest 0:02:12.840 --> 0:02:17.720 grade of inflation. And if anything, that maybe understates some 0:02:17.760 --> 0:02:21.400 of what we've got coming down the pipe, because that's 0:02:21.639 --> 0:02:25.640 looking at the looking at the rate increases for everybody, 0:02:25.680 --> 0:02:27.840 and of course the rating increases will be most severe 0:02:27.880 --> 0:02:31.359 for those who've experienced natural disasters and some of that, 0:02:31.840 --> 0:02:34.840 some of what we're seeing there is extremely severe, and 0:02:34.919 --> 0:02:37.840 I think particularly if you look at what's being paid 0:02:37.840 --> 0:02:44.080 by reinsurers, the cost of to renew policies for reinsurers 0:02:44.360 --> 0:02:48.960 is fifty percent in the US and in Australia, if 0:02:48.960 --> 0:02:52.760 you've been exposed to disasters, it's going up seventy five percent. 0:02:53.000 --> 0:02:55.920 So there's some really extraordinary increases that we're seeing at 0:02:55.919 --> 0:02:59.760 the moment. Even insurance you hadn't had catastrophic disasters, we're 0:02:59.760 --> 0:03:02.720 having to pay twenty percent more than a year ago. 0:03:03.120 --> 0:03:06.520 And that cost which is you know, remember the structure 0:03:06.520 --> 0:03:09.160 of insurance. You have you take out a policy with 0:03:09.200 --> 0:03:12.120 your insurer, and then your insurer takes out a policy 0:03:12.120 --> 0:03:14.840 with a reinsurer to cover the really big costs from 0:03:15.080 --> 0:03:18.160 from the big natural disasters that they struggle to cover 0:03:18.200 --> 0:03:21.200 on their own. The pricing that they are paying to 0:03:21.240 --> 0:03:24.760 reinsurre as gets you know, gets knocked on down down 0:03:24.800 --> 0:03:26.520 the track. If they're having to pay a lot extra 0:03:26.560 --> 0:03:28.799 to reinsure as they're having to get a lot lot 0:03:28.880 --> 0:03:32.320 extra on your premiums or alternatively, they're having to exclude 0:03:32.360 --> 0:03:36.360 things the previously they didn't exclude. And of course we're 0:03:36.360 --> 0:03:38.520 also seeing as a result of this a lot of 0:03:38.520 --> 0:03:41.000 people who just simply can't really afford insurance anymore. 0:03:41.160 --> 0:03:44.320 So is this because of the natural disasters that we've 0:03:44.320 --> 0:03:45.000 seen of late. 0:03:45.360 --> 0:03:48.840 I'm going to reach for a classic insurance disaster industry 0:03:48.880 --> 0:03:54.000 cliche and say it is a perfect storm, But there 0:03:54.080 --> 0:03:56.760 is a combination of several factors that are happening at 0:03:56.760 --> 0:04:01.160 the same time. They're actually the actual disasters that we've 0:04:01.160 --> 0:04:06.560 seen recently, they're because of climate change and also generally 0:04:06.640 --> 0:04:10.400 just because insurance losses always rise, because they rise with income, 0:04:10.440 --> 0:04:14.240 they rise with population growth, they rise with people putting 0:04:14.240 --> 0:04:16.840 more of their money into the capital stock of their 0:04:16.880 --> 0:04:20.440 buildings and things like that. Insurance costs always rise. But 0:04:20.480 --> 0:04:22.679 we've seen, you know, we've seen a run of record 0:04:22.720 --> 0:04:25.440 years in recent years that the most recent big disaster 0:04:25.480 --> 0:04:28.520 obviously in the US hurricane dial it doesn't seem to 0:04:28.560 --> 0:04:32.320 have been actually a particularly dramatic one. I think the 0:04:33.480 --> 0:04:36.359 modeling now is suggesting it's sort of low single digits 0:04:36.360 --> 0:04:38.520 of billions. Sounds like a lot of money, but for 0:04:38.520 --> 0:04:42.760 the insurance industry, that's pretty that's pretty small potatoes. That 0:04:42.960 --> 0:04:47.839 in itself is not that much to worry about, so yes, 0:04:47.960 --> 0:04:51.320 but I think the other factors to consider is a 0:04:51.320 --> 0:04:54.880 lot of the sort of macroeconomic factors that come in here. 0:04:55.240 --> 0:04:59.520 For most of the period that we've been growing more 0:04:59.520 --> 0:05:02.640 concerned seeing some of these bigger impacts from climate change, 0:05:02.800 --> 0:05:04.840 it's been over the past fifteen years when interest rates 0:05:04.880 --> 0:05:07.719 have been very low and when inflation has been very low, 0:05:08.600 --> 0:05:11.880 And the one thing that insurers and reinsurers worry about 0:05:11.880 --> 0:05:16.719 more than climate change and natural disasters is inflation. The 0:05:16.760 --> 0:05:19.440 reason for that, if you think about the model when 0:05:19.480 --> 0:05:23.960 you pay your insurance premiums, the insurer does not expect 0:05:23.960 --> 0:05:26.840 to pay out your losses if something happens to your 0:05:26.880 --> 0:05:30.760 house from the money that you pay them. The way 0:05:30.800 --> 0:05:32.800 the model works is they take your premiums and they 0:05:32.839 --> 0:05:36.320 invest it and they can only you know, they can 0:05:36.360 --> 0:05:40.480 only cover your losses based on the investment returns and 0:05:40.520 --> 0:05:45.320 what they're investing in because their conservative conservative investors is bonds. 0:05:46.080 --> 0:05:48.000 And of course, so the bond bull market of the 0:05:48.000 --> 0:05:51.520 past fifteen years had been you know, was immensely good 0:05:51.520 --> 0:05:56.520 for the insurance industry, and that although consumers probably didn't 0:05:56.560 --> 0:05:59.440 feel that way, that meant the insurers were pretty lenient 0:05:59.520 --> 0:06:02.359 over the past sort of ten to fifteen years, you know, 0:06:02.400 --> 0:06:06.880 to householders, to people with insured property. This has now changed. 0:06:07.160 --> 0:06:09.920 The bond billmark is over. You've got this, you've got 0:06:10.000 --> 0:06:13.200 high rates of inflation, which are meaning on their investment portfolios, 0:06:13.440 --> 0:06:15.560 a lot of them are making losses. They're certainly not 0:06:15.600 --> 0:06:18.520 making good you know, good returns on those portfolios to 0:06:19.000 --> 0:06:22.080 cover the losses that they have to pay out. And 0:06:22.120 --> 0:06:25.480 another fact that we have, of course, is that the 0:06:26.160 --> 0:06:29.240 period of very low interest rates has has come to 0:06:29.279 --> 0:06:31.920 an end, and that means that there was over the 0:06:32.000 --> 0:06:35.320 last fifteen years, there were a lot of different types 0:06:35.360 --> 0:06:38.200 of investors that were getting into the insurance industry in 0:06:38.279 --> 0:06:41.799 their search for different for better yield. So you would 0:06:41.800 --> 0:06:44.200 have you know, hedge funds, you know, there were a 0:06:44.240 --> 0:06:48.320 lot of you know, bond investors, catastrophe bonds, sovereign wealth funds, 0:06:48.320 --> 0:06:51.600 pension funds, all sorts of new investors were coming in 0:06:51.680 --> 0:06:54.440 and that was providing capital to the insurance industry, and 0:06:54.480 --> 0:06:57.599 that allowed them to push down or compete down the 0:06:57.600 --> 0:07:00.880 premiums that we were paying. Interest rates have gone up. 0:07:00.920 --> 0:07:04.680 It's a lot easier for those investors to find yield elsewhere, 0:07:04.920 --> 0:07:07.560 so they're not going to the insurance industry. So again 0:07:07.960 --> 0:07:11.400 that has that has been its big macroeconomic factor. As 0:07:11.440 --> 0:07:15.080 we've moved from a low rate, low inflation environment to 0:07:15.120 --> 0:07:17.960 a high rate, high inflation environment, some of those macro 0:07:18.040 --> 0:07:20.400 factors that made insurance more affordable for the past fifteen 0:07:20.480 --> 0:07:24.920 years have disappeared as a result of what insurers are 0:07:24.960 --> 0:07:27.520 having to do is pass the costs back on to householders. 0:07:27.680 --> 0:07:31.080 We're talking with Bloomberg opinion columnist David Fickling about how 0:07:31.320 --> 0:07:35.920 severe weather is a perfect storm for the insurance industry. David, 0:07:35.960 --> 0:07:37.160 have we seen this before? 0:07:38.320 --> 0:07:44.119 Well, the inflationary situation, I mean, we're this is sounding 0:07:44.200 --> 0:07:46.760 slightly long in the tooth reference, but there was you know, 0:07:46.880 --> 0:07:50.120 during the last period of high inflation that you saw 0:07:50.360 --> 0:07:54.000 in the sort of early to mid eighties, there was 0:07:54.040 --> 0:07:57.520 a real significant crisis for the insurance industry connected to 0:07:57.560 --> 0:07:59.000 that because it did a lot of damage to their 0:07:59.000 --> 0:08:04.520 investment folios. At that point. It was you know, it 0:08:04.560 --> 0:08:07.960 was also accentuated by some of the you know, quite 0:08:07.960 --> 0:08:11.000 big unusual losses that came in around about the eighties. 0:08:11.040 --> 0:08:13.680 Of course, we had we had the period of things 0:08:13.680 --> 0:08:18.160 like asbestosis, uh, you know, a lot of insurers found 0:08:18.200 --> 0:08:23.200 that they they had cover for asbestos damage, but they 0:08:23.200 --> 0:08:25.800 weren't they you know, they hadn't really modeled those risks 0:08:25.840 --> 0:08:28.680 because that you know, the problems with asbestos weren't known 0:08:28.720 --> 0:08:30.840 until then. A lot of money was paid at There 0:08:30.840 --> 0:08:32.840 are a lot of big disasters in the late eighties, 0:08:32.880 --> 0:08:36.320 sort of oil tanker disasters, the you know, the the 0:08:36.559 --> 0:08:40.600 x on Valdis, the Tory Canyon I think, and most 0:08:40.679 --> 0:08:45.199 famously what you know, what I ended up resulting from 0:08:45.280 --> 0:08:49.240 that sort of series of of of linked disasters that 0:08:49.160 --> 0:08:51.560 that you know, the Lloyds of London, the you know, 0:08:51.600 --> 0:08:55.400 the original sort of shipping insurance market that's been been 0:08:55.480 --> 0:08:59.480 running from three hundred years, suffered an absolute crisis that 0:08:59.520 --> 0:09:02.080 caused a lot of the syndicates there at Lloyd's to 0:09:02.080 --> 0:09:02.680 lose a great. 0:09:02.559 --> 0:09:03.160 Deal of money. 0:09:03.960 --> 0:09:06.120 So the insurance industry has been through this sort of 0:09:06.120 --> 0:09:08.920 thing before, and it's a reason why they're very, very 0:09:08.960 --> 0:09:12.440 wary of inflation because of what it's done to them 0:09:12.440 --> 0:09:15.280 in the past. Now I think what we're going to see, 0:09:15.360 --> 0:09:18.640 I mean, insurers and reinsurers are very circumspect about their 0:09:19.240 --> 0:09:23.960 job is managing future risks and they're very good at it. 0:09:24.679 --> 0:09:27.320 And of course the way they do it is something 0:09:27.360 --> 0:09:30.960 that we tend to forget and don't like very much, 0:09:30.960 --> 0:09:33.800 which is that they just stop insuring risks. They either 0:09:33.840 --> 0:09:36.240 price risks so high that we can't afford them, or 0:09:36.280 --> 0:09:40.040 they just withdraw coverage altogether from areas. And I think 0:09:40.040 --> 0:09:42.840 we tend to think. I mean, you'd often have heard 0:09:42.880 --> 0:09:45.440 I think over the past ten years, people talking about 0:09:46.160 --> 0:09:49.120 climate and insurance saying, well, we have you know, the 0:09:49.120 --> 0:09:51.600 insurance industry is a great model for sort of you know, 0:09:51.640 --> 0:09:54.480 for pricing risks and that will sort of take away 0:09:54.480 --> 0:09:56.680 the risk of climate change. Well, it doesn't take away 0:09:56.720 --> 0:09:59.480 the risk. It moves the risk around and the insurance 0:09:59.520 --> 0:10:03.120 industry to be always making a profit. And if those 0:10:03.240 --> 0:10:05.559 risks get so high that it's not making a profit, 0:10:06.000 --> 0:10:09.520 then the insurance industry will withdraw. If you look at Florida, 0:10:09.559 --> 0:10:12.120 for instance, is the classic example, although if you look 0:10:12.160 --> 0:10:16.000 at the insurance market there it is completely broken. Less 0:10:16.000 --> 0:10:19.400 than one in five Floridians have flood protection in their 0:10:19.440 --> 0:10:22.200 insurance policies. Bear in mind, another effect that we have 0:10:22.280 --> 0:10:25.480 from inflation is that the cost of rebuilding is going 0:10:25.520 --> 0:10:29.720 up very dramatically. So even if you thought you had 0:10:29.840 --> 0:10:32.840 enough money to rebuild your house five years ago, you 0:10:32.840 --> 0:10:35.040 probably don't have enough money to rebuild your house now. 0:10:36.480 --> 0:10:40.800 So all of those factors mean that people who previously 0:10:40.800 --> 0:10:43.480 thought they were sort of under the protective umbrella of 0:10:43.679 --> 0:10:48.360 insurance really finding the umbrella rather threadbare at this point. 0:10:48.520 --> 0:10:52.080 Bloomberg Opinion columnist David Fickling coming up. We're going to 0:10:52.080 --> 0:10:54.600 continue this conversation from a different point of view. What 0:10:54.760 --> 0:10:58.320 have we learned about, say, manufactured housing and severe weather 0:10:58.400 --> 0:11:01.480 and what needs to be done for those That's just ahead. 0:11:01.800 --> 0:11:03.360 You're listening to Bloomberg Opinion. 0:11:11.800 --> 0:11:15.599 You're listening to the Bloomberg Opinion podcast. Catch us Saturdays 0:11:15.640 --> 0:11:18.800 at one and seven pm Eastern on Bloomberg dot Com, 0:11:18.840 --> 0:11:21.960 the iHeartRadio app, and the Bloomberg Business App, or listen 0:11:22.040 --> 0:11:24.280 on demand wherever you get your podcasts. 0:11:26.160 --> 0:11:29.480 You're listening to Bloomberg Opinion. I'm Amy Morris. We are 0:11:29.520 --> 0:11:33.160 talking about the aftermath of severe weather and the impact 0:11:33.280 --> 0:11:38.440 on manufactured homes. Before Hurricane Adalia slammed into Florida, the 0:11:38.440 --> 0:11:41.800 mayor of Tampa, Jane Caster, was warning residents in low 0:11:41.880 --> 0:11:46.000 lying neighborhoods and in mobile homes to get out. Understand 0:11:46.040 --> 0:11:48.080 that Mother nature wins every time. 0:11:48.160 --> 0:11:51.320 So if you have the opportunity to evacuate, and you can, 0:11:51.760 --> 0:11:54.600 you should, please please do. 0:11:54.960 --> 0:11:58.760 After Hurricane Adalia, some of the most endearing images are 0:11:58.840 --> 0:12:02.840 of mobile and manu factored homes battered and flood damaged. 0:12:03.120 --> 0:12:06.160 So what can be done to protect these manufactured homes 0:12:06.160 --> 0:12:09.400 and why do they even need protecting. Let's bring in 0:12:09.480 --> 0:12:13.480 Bloomberg opinion columnist Jonathan Levin, who covers finance markets and 0:12:13.720 --> 0:12:17.839 M and A Jonathan. Manufactured in mobile homes absolutely are 0:12:17.920 --> 0:12:20.640 affordable homes. But just bring us up to speed. How 0:12:20.640 --> 0:12:23.000 many people live in these homes? Let's start there. 0:12:23.280 --> 0:12:26.920 Yeah, millions and millions, and it's even a greater share 0:12:27.080 --> 0:12:32.640 of Floridians. So you know, we're talking six seven percent 0:12:32.679 --> 0:12:37.160 of occupied housing stock here in the Sunshine State. And 0:12:37.640 --> 0:12:39.439 you know, it's important to say that it's a really, 0:12:39.480 --> 0:12:43.280 really important source of housing here in the Sunshine State 0:12:43.320 --> 0:12:48.280 and across the sun Belt where affordability has become more 0:12:48.320 --> 0:12:50.120 and more of a challenge in recent years. 0:12:50.480 --> 0:12:53.559 You say, lawmakers should improve the planning and the oversight 0:12:53.640 --> 0:12:56.720 of these mobile home parks, Like what what is lacking? 0:12:57.400 --> 0:12:59.320 Yeah, so a couple of things. 0:12:59.640 --> 0:13:05.000 So a uh, you know, manufactured housing tends to be 0:13:05.040 --> 0:13:08.240 subject to a lot of nimbiism. It's this this sort 0:13:08.280 --> 0:13:11.920 of entrenched nimbism in in a lot of municipal codes. 0:13:12.200 --> 0:13:15.800 And because of that, manufactured housing tends to end up 0:13:15.840 --> 0:13:19.840 in places like you know, unincorporated parts of the of 0:13:20.200 --> 0:13:21.199 various counties. 0:13:21.520 --> 0:13:21.760 Uh. 0:13:22.160 --> 0:13:27.480 Right, So these also, not so coincidentally, can often be 0:13:27.559 --> 0:13:30.880 some of the most vulnerable parts of the county do 0:13:31.280 --> 0:13:35.040 to climate change. So I think the very first thing 0:13:35.800 --> 0:13:40.560 that that lawmakers and other leaders in our communities need 0:13:40.640 --> 0:13:44.080 need to consider is that manufactured housing needs to be 0:13:44.400 --> 0:13:46.800 a part of the plan from the beginning. It can't 0:13:46.840 --> 0:13:48.719 just be this this afterthought. 0:13:48.960 --> 0:13:49.160 Uh. 0:13:49.200 --> 0:13:52.120 And and it can't uh it just be you know, 0:13:52.280 --> 0:13:54.880 cast off to the these sort of no man's lands, 0:13:54.960 --> 0:13:59.400 because like wealthier communities, I don't want to don't want to. 0:13:59.320 --> 0:13:59.800 Look at it. 0:13:59.800 --> 0:14:03.360 That's it's not a sustainable and it's not a safe 0:14:04.080 --> 0:14:07.240 solution for this kind of housing. The key point here 0:14:07.360 --> 0:14:10.319 is some of these structures are actually very very good. 0:14:11.360 --> 0:14:14.880 If you look at the kind of manufactured housing that 0:14:14.960 --> 0:14:19.320 has come out since nineteen ninety four, since a critical 0:14:19.560 --> 0:14:23.840 revision in the way the federal regulations were these kinds 0:14:23.840 --> 0:14:28.120 of structures are actually pretty good, and they're just as 0:14:28.160 --> 0:14:32.520 good as anything else when it comes to flood specifically. 0:14:32.880 --> 0:14:35.360 Again, the issue is when. 0:14:36.640 --> 0:14:40.480 You community biases come into play and these sorts of 0:14:40.520 --> 0:14:44.160 housing get cast off into the middle of nowhere, then 0:14:44.200 --> 0:14:47.360 you have these communities which tend to skew a little 0:14:47.360 --> 0:14:50.920 bit lower income and are inherently vulnerable. Because of that, 0:14:51.360 --> 0:14:53.640 you have them placed in some of the most vulnerable 0:14:53.720 --> 0:14:58.080 jurisdictions in various counties and states. 0:14:58.480 --> 0:15:02.360 The conventional wisdom is all so that it's not safe. 0:15:02.400 --> 0:15:06.360 You were just addressing that that that's sort of an 0:15:06.360 --> 0:15:10.800 overgeneralization that maybe tornadoes are not going to look for 0:15:10.840 --> 0:15:14.640 the trailer parkin and target it, which is an ongoing joke. 0:15:14.680 --> 0:15:16.880 I'm from South Carolina, so I remember those jokes a 0:15:16.880 --> 0:15:19.800 lot where we had, you know, areas where folks were 0:15:19.840 --> 0:15:23.240 living in mobile homes or manufactured housing, and those seemed 0:15:23.280 --> 0:15:25.840 to be the ones that were the most vulnerable. Your 0:15:25.880 --> 0:15:28.800 point being, it's not the trailer, it's not the house, 0:15:28.840 --> 0:15:31.600 it's not the manufactured housing that's vulnerable. It's the location. 0:15:32.160 --> 0:15:35.320 Yeah, there's that, and there's a couple of other things. 0:15:35.560 --> 0:15:38.520 So Another thing that I talk about my recent piece 0:15:38.840 --> 0:15:42.520 is sort of aligning economic incentives. A key problem with 0:15:42.640 --> 0:15:47.720 manufactured housing is that oftentimes while residents will own the structure, 0:15:47.880 --> 0:15:51.160 they will not own the land right They're oftentimes found 0:15:51.160 --> 0:15:56.880 in these parks, and residents are essentially renters there. So 0:15:57.080 --> 0:16:01.200 if you do have an unscrupulous landlord who just wants 0:16:01.280 --> 0:16:05.800 to pinch pennies and maximize profits and doesn't invest in 0:16:06.440 --> 0:16:11.040 the right sort of infrastructure and storm preparedness, that can 0:16:11.200 --> 0:16:15.960 also be a problem area. So you know, as part 0:16:15.960 --> 0:16:19.600 of the solutions that I sort of propose and review 0:16:19.640 --> 0:16:23.200 in my piece, I suggest that there really also needs 0:16:23.240 --> 0:16:27.720 to be increased oversight of landlords. You know, this has 0:16:27.800 --> 0:16:32.200 been a popular investment for private equity. 0:16:32.320 --> 0:16:33.840 It's a private it's. 0:16:33.680 --> 0:16:37.320 A popular investment for reds, And I'm not saying that 0:16:38.000 --> 0:16:41.640 all or even most of them are bad actors, but 0:16:42.280 --> 0:16:48.280 in an environment where the economic incentives aren't necessarily aligned 0:16:48.680 --> 0:16:51.400 all the time, you do need government to come in 0:16:51.440 --> 0:16:53.720 and make sure that everybody is acting properly. 0:16:54.120 --> 0:16:57.440 And we are talking with Bloomberg opinion columnist Jonathan Levin 0:16:57.480 --> 0:17:00.000 about the role of manufactured homes in the US and world, 0:17:00.040 --> 0:17:05.360 why they need protecting. You mentioned community planning and how 0:17:05.400 --> 0:17:09.919 it needs to document and corporate manufactured home communities, giving 0:17:09.960 --> 0:17:16.960 them more of a footprint, more stability within those planned communities. 0:17:17.080 --> 0:17:18.919 Is that going to get any attraction? I mean, like 0:17:18.960 --> 0:17:22.000 you say, there's this sort of attitude about mobile homes 0:17:22.160 --> 0:17:23.680 that isn't always very flattering. 0:17:24.280 --> 0:17:27.000 I think you know, one key solution, one key longer 0:17:27.119 --> 0:17:31.160 term solution to all of this is potentially to give 0:17:32.240 --> 0:17:37.800 manufacture housing residents more self determination. So again I make 0:17:37.880 --> 0:17:41.920 the point that there's this problem of aligning the economics 0:17:42.000 --> 0:17:45.399 incentive so that people want to invest in resilience, and 0:17:45.440 --> 0:17:48.200 one way to do that is to give them ownership 0:17:48.240 --> 0:17:50.760 of that plot of land. So a lot of times 0:17:50.760 --> 0:17:53.280 what happens, and what can be be a dangerous situation 0:17:53.560 --> 0:17:58.240 is a park gets sold and somebody comes in and 0:17:58.280 --> 0:18:02.160 they want to start pinching pens these What if, you know, 0:18:02.440 --> 0:18:07.879 when parks get sold, the government requires the seller to 0:18:09.160 --> 0:18:11.880 consider an offer from the community. What if the community 0:18:11.920 --> 0:18:17.080 could could come in and you know, pool their money 0:18:17.160 --> 0:18:20.400 and make an offer themselves, then you have better alignment 0:18:20.440 --> 0:18:22.800 of economic incentives. You have a group of people who 0:18:22.920 --> 0:18:27.920 want to invest in the resilience of their terrain, and 0:18:27.520 --> 0:18:30.960 there's some really good research that suggests that that can 0:18:31.000 --> 0:18:32.240 be a good long term solution. 0:18:32.840 --> 0:18:36.400 Is there a need for government then to intervene here? 0:18:37.000 --> 0:18:37.320 Correct? 0:18:37.400 --> 0:18:40.520 Yeah, So some of the best laws that have been 0:18:40.560 --> 0:18:44.720 going on the books recently do a couple of things. 0:18:44.880 --> 0:18:48.760 So they will say that when a piece of property 0:18:49.000 --> 0:18:53.440 is going up for sale, residents should be alerted in advance, right, 0:18:53.680 --> 0:18:56.639 you know, you can't give somebody forty eight hours to 0:18:56.680 --> 0:19:01.679 bring the community together and make an offer. The government 0:19:02.720 --> 0:19:07.240 and authorities in general should also be given advance notice, 0:19:07.720 --> 0:19:12.679 and it's important to have some sort of requirement that 0:19:12.680 --> 0:19:16.480 that fair consideration is actually given to the community's offer. 0:19:16.600 --> 0:19:20.560 So one form that that can take again is a 0:19:19.960 --> 0:19:21.840 right of first refusal. 0:19:22.880 --> 0:19:25.959 You also mentioned nimbiism a couple of times earlier in 0:19:26.000 --> 0:19:29.640 this interview. Perhaps part of the solution is the rest 0:19:29.640 --> 0:19:31.719 of us changing our attitudes. 0:19:32.680 --> 0:19:33.440 Yeah, exactly. 0:19:33.720 --> 0:19:37.320 I mean, so manufactured housing, it's important to point out 0:19:37.359 --> 0:19:38.679 at the end here it's. 0:19:38.560 --> 0:19:41.000 A really really broad category and if you. 0:19:40.960 --> 0:19:43.199 Look at some of these structures, you wouldn't know that 0:19:43.240 --> 0:19:46.880 they are that they are manufactured housing. 0:19:47.160 --> 0:19:49.840 These are not, you know, trailer parks. 0:19:49.880 --> 0:19:56.399 Classically, classically speaking, and so yeah, it's you know, manufactured 0:19:56.440 --> 0:19:59.280 housing is going to be an important part of our 0:19:59.280 --> 0:20:04.760 affordable hoigh housing challenges here in the United States, and 0:20:05.040 --> 0:20:09.679 it's important to embrace it as as such and not 0:20:09.880 --> 0:20:12.800 bring so many biases to the debate to start with. 0:20:13.200 --> 0:20:16.640 Jonathan Levin is a Bloomberg opinion columnist who covers finance, 0:20:16.680 --> 0:20:18.840 markets and M and A and don't forget We are 0:20:18.880 --> 0:20:22.520 available as a podcast on Apple, Spotify or your favorite 0:20:22.560 --> 0:20:26.760 podcast platform. The alcohol industry has been thriving despite a 0:20:26.840 --> 0:20:30.680 streak of threats, the legalization of marijuana, a trade war 0:20:30.760 --> 0:20:33.879 with China that has hampered US exports, the rise of 0:20:33.920 --> 0:20:37.880 the sober curious movement, and now a new risk one 0:20:38.000 --> 0:20:41.720 few investors or companies are publicly acknowledging could pressure sales, 0:20:41.920 --> 0:20:45.159 and that is weight loss drugs. Lisa Jarvis is a 0:20:45.200 --> 0:20:49.720 Bloomberg opinion columnist. She covers biotech, healthcare, and the pharmaceutical industry, 0:20:50.000 --> 0:20:53.040 and she joins us Now, Lisa, we know these weight 0:20:53.080 --> 0:20:57.080 loss drugs are reshaping the weight loss market. How is 0:20:57.119 --> 0:21:01.000 there a threat now or an impact to the market 0:21:01.000 --> 0:21:02.240 for alcoholic beverages. 0:21:02.800 --> 0:21:06.680 It's this unexpected side effect of these drugs which is 0:21:06.720 --> 0:21:10.639 that people just don't really have the desire to drink. 0:21:10.720 --> 0:21:13.640 Not all people, but a healthy chunk of them. One 0:21:13.680 --> 0:21:17.560 survey said that about sixty two percent of people who 0:21:17.640 --> 0:21:21.640 take these drugs drink less alcohol. I think two things 0:21:21.640 --> 0:21:25.040 are going on, you know. One is that they just 0:21:25.760 --> 0:21:29.639 make alcohol less appealing or any addictive substances, including food, 0:21:29.920 --> 0:21:33.919 less appealing. And then two, I think you feel full faster, 0:21:34.119 --> 0:21:36.560 So even if you kind of force yourself to drink it, 0:21:36.840 --> 0:21:39.520 you can't have more than one drink before it is 0:21:39.600 --> 0:21:40.800 really unpleasant for you. 0:21:41.920 --> 0:21:48.480 So food, nicotine, alcohol, opioids, those sort of addictive substances. 0:21:48.520 --> 0:21:50.600 And you were the one who said that food can 0:21:50.640 --> 0:21:54.280 be an addictive substance, And as a layman, I would say, yeah, 0:21:54.359 --> 0:21:58.159 it's probably true. It dampens the rewards that goes up 0:21:58.200 --> 0:22:00.800 into your brain and it says this isn't pleasant for you. 0:22:00.880 --> 0:22:01.719 Is that how it works? 0:22:02.119 --> 0:22:06.679 That's right. It's dampening the kind of rewards circustry circuitry 0:22:06.720 --> 0:22:11.359 in our brains that tells us to keep going. And 0:22:11.840 --> 0:22:13.840 you know that kind of hit you get when you 0:22:13.920 --> 0:22:16.679 eat something in sugary, or you know, you have a 0:22:16.680 --> 0:22:22.119 glass of alcohol, or I suppose smoke a cigarette and 0:22:22.200 --> 0:22:26.080 so it's it's affecting that particular circuitry in the brain, 0:22:26.200 --> 0:22:28.359 and they think that's why it is that we're seeing 0:22:28.400 --> 0:22:31.760 the side effect that you know, I would say for 0:22:31.800 --> 0:22:34.280 some people that's a happy side effect. I've talked to 0:22:34.320 --> 0:22:36.480 a lot of people now who are taking these drugs, 0:22:36.920 --> 0:22:41.760 and some of them thought that one added bonus of 0:22:41.800 --> 0:22:43.720 going on them was the fact that it could help 0:22:43.760 --> 0:22:45.880 them kind of get their drinking a little more in check, 0:22:46.080 --> 0:22:47.600 especially coming off of the pandemic. 0:22:48.000 --> 0:22:52.120 I wonder if these drugs, the the ozebic and these 0:22:52.160 --> 0:22:56.199 weight loss drugs could be used then for addicts, like 0:22:56.240 --> 0:23:00.479 maybe marketed to physicians or to a clinic ex fo 0:23:00.720 --> 0:23:04.240 addicts who maybe really are looking for a way out 0:23:04.280 --> 0:23:04.840 and for help. 0:23:06.080 --> 0:23:08.520 Yeah, I mean, there definitely are studies going on. There's 0:23:08.520 --> 0:23:11.440 some researchers at the University of North Carolina that are 0:23:11.480 --> 0:23:15.200 looking at this. They're conducting clinical studies to sort of say, Okay, 0:23:15.640 --> 0:23:19.600 you know, here's how well they work for different substances 0:23:19.760 --> 0:23:22.960 for people who have substance use disorder. And I think 0:23:23.000 --> 0:23:25.720 that kind of paves the way we have good data 0:23:25.800 --> 0:23:30.960 in a different various animal models. I think rats, mice, monkeys, 0:23:31.080 --> 0:23:34.359 monkeys are a lot like humans, and so you know, 0:23:34.720 --> 0:23:37.480 and then we've got just at this point, scads of 0:23:37.520 --> 0:23:40.160 anecdotal data. Like I said, I've talked to a lot 0:23:40.160 --> 0:23:42.280