WEBVTT - It's 9 O'Clock Somewhere 0:00:03.800 --> 0:00:07.120 Welcome to Bloomberg Opinion. I'm Vonnie Quinn this week, if 0:00:07.160 --> 0:00:11.119 the FIT successfully engineers a soft landing that does involve 0:00:11.240 --> 0:00:14.120 companies having to pay more to borrow for quite an 0:00:14.160 --> 0:00:17.680 extended period of time and finding it that much harder 0:00:17.720 --> 0:00:20.279 to pass costs on. John author Is on how a 0:00:20.320 --> 0:00:23.360 soft landing for the economy does not mean a soft 0:00:23.440 --> 0:00:27.680 landing necessarily for markets. Also Alexis Leanders and how exactly 0:00:27.680 --> 0:00:29.800 you can be making a quarter of a million dollars 0:00:29.840 --> 0:00:33.240 a year and still be living paycheck to paycheck. Later, 0:00:33.280 --> 0:00:35.720 we'll speak with Stephen Mim on the history of remote work. 0:00:35.760 --> 0:00:38.600 As the number of workers back in offices drops once again, 0:00:39.040 --> 0:00:42.880 it's partially due to a COVID resurgence. Sure Another factor, though, 0:00:43.120 --> 0:00:46.000 the fear of crime in big cities such as New York. 0:00:46.200 --> 0:00:48.760 So let's kick off this week with Justin Fox. He's 0:00:48.800 --> 0:00:51.640 been digging into the available data for some clarity on 0:00:51.760 --> 0:00:54.959 just how dangerous our metropolis is. So Justin I think 0:00:54.960 --> 0:00:57.080 there's a bit of a trope out there that crime 0:00:57.280 --> 0:00:58.960 is higher in New York City and that perhaps even 0:00:59.000 --> 0:01:01.240 the city is going back to the nineteen eighties. Is 0:01:01.240 --> 0:01:04.039 there any truth to that crime is higher in the city. 0:01:04.319 --> 0:01:07.640 Basically as people emerge from the lockdown. In two thousand twenty, 0:01:07.840 --> 0:01:11.240 murders and shooting shot up really dramatically. Other crime didn't. 0:01:11.920 --> 0:01:15.120 Now the murders and shootings are starting to decline a little. 0:01:15.160 --> 0:01:19.920 Other crimes are up, but it's still miles away from 0:01:20.200 --> 0:01:23.320 the sort of homicide rates that New York had in 0:01:23.360 --> 0:01:27.039 the nineteen eighties or early nineties. Some big cities it 0:01:27.200 --> 0:01:31.080 is back to about as bad as it was then, Philadelphia, Chicago. 0:01:31.560 --> 0:01:33.520 But it's kind of funny, is not New York, not 0:01:33.840 --> 0:01:36.160 l A, which seemed to be the place is getting 0:01:36.200 --> 0:01:39.760 the most publicity about crime exactly. So you write that 0:01:39.800 --> 0:01:42.400 the rate is still less than a fifth of what 0:01:42.440 --> 0:01:44.320 it was in I think a lot of people would 0:01:44.319 --> 0:01:46.520 be really really surprised to hear that, but it's not 0:01:46.560 --> 0:01:49.200 the case all over the country. You dug into the 0:01:49.240 --> 0:01:54.000 CDC's wonder databases. Tell us a little bit about these wonderments. Yeah, 0:01:54.040 --> 0:01:56.560 I I mean, I'd heard about them before the pandemic, 0:01:56.600 --> 0:01:59.880 but I first waited into them sadly not long after 0:02:00.000 --> 0:02:04.279 the pandemic started. And um, it's a remarkable, if pretty 0:02:04.360 --> 0:02:08.520 confusing at first, set of databases that, among other things 0:02:08.520 --> 0:02:11.720 allow you to just look at all causes of death 0:02:12.280 --> 0:02:14.600 in the US. You can sort it by cause of death, 0:02:14.680 --> 0:02:16.520 you can sort it by place, you can sort it 0:02:16.520 --> 0:02:19.640 by year, you can sort it by demographic groups. And 0:02:19.680 --> 0:02:21.880 of course you did all of that, and what conclusions 0:02:21.880 --> 0:02:24.440 did you come to in terms of things like location 0:02:24.520 --> 0:02:27.680 and how that matters, or incomes and how that matters. Well, 0:02:27.800 --> 0:02:31.240 what I did for this particular exercises, I was looking 0:02:31.280 --> 0:02:34.720 at homicide rates. Normally it's the suburban counties and large 0:02:34.720 --> 0:02:38.120 metorias have the lowest homicide rates most years. New York 0:02:38.200 --> 0:02:41.040 City has had actually fallen below even that for a 0:02:41.080 --> 0:02:43.640 couple of years before the pandemic. Since the pandemic it's 0:02:43.680 --> 0:02:45.920 slightly higher. But you know, New York City has a 0:02:45.960 --> 0:02:49.600 lower homicide rate than rural America. Even now, subdansolutely lower. 0:02:50.120 --> 0:02:52.200 And then I just started thinking about one of the 0:02:52.240 --> 0:02:55.400 things people are very concerned about right now and with reason, 0:02:55.960 --> 0:02:58.440 is that the subways seems more dangerous than it was 0:02:58.440 --> 0:02:59.960 a couple of years ago, and it is more dane 0:03:00.040 --> 0:03:02.000 dress than it was a couple of years ago. Basically, 0:03:02.160 --> 0:03:04.920 overall crime levels in the subway about the same, but 0:03:05.520 --> 0:03:08.720 ridership is about less so if you're riding at the 0:03:08.800 --> 0:03:11.600 higher risk of crime, I think this way, and I 0:03:11.600 --> 0:03:13.239 think a lot of people don't. But when I think 0:03:13.280 --> 0:03:15.680 about the subway and the risks I faced in there, 0:03:15.680 --> 0:03:18.000 I also think about things like tee, what if I 0:03:18.040 --> 0:03:20.760 had to drive on the freeway in Houston all the time. 0:03:20.960 --> 0:03:24.560 You throw in transport accidents, which is a grab bag 0:03:24.639 --> 0:03:27.639 of mostly car crashes, but also I guess you could 0:03:27.680 --> 0:03:31.400 tip over your tractor or whatever. And you put the 0:03:31.440 --> 0:03:34.480 two together and suddenly New York City goes to being 0:03:34.600 --> 0:03:38.840 much safer than any other broad classification, three times safer 0:03:38.880 --> 0:03:42.720 than rural and small town America. Brooklyn and the Bronx 0:03:42.880 --> 0:03:46.440 come in a respectable forty one, twenty seventh place in 0:03:46.520 --> 0:03:49.840 the country's mortality rankings. Did you expect that? Um? I 0:03:50.000 --> 0:03:53.440 was a little surprised, and that the difficulty. One of 0:03:53.520 --> 0:03:55.960 the things that the CDC does is it knows everything 0:03:56.000 --> 0:03:59.240 about mortality, but it won't tell you everything. So if 0:03:59.280 --> 0:04:03.280 there are fewer than ten deaths in a county, it 0:04:03.440 --> 0:04:06.120 just doesn't disclose it at all because it is afraid 0:04:06.200 --> 0:04:08.040 that you can figure out who they were. So what 0:04:08.120 --> 0:04:11.320 I did, I then went beyond traffic accidents and looked 0:04:11.360 --> 0:04:14.480 at other external causes of death, which you know. You 0:04:14.600 --> 0:04:17.360 look through the list and there's things like being bitten 0:04:17.400 --> 0:04:20.640 by a snake or drowning in the pool, and most 0:04:20.720 --> 0:04:24.600 of those seem less likely to befall you in New 0:04:24.680 --> 0:04:27.680 York City than other places. They're bitten by rats is 0:04:27.760 --> 0:04:32.760 in there too, which yeah, exactly, I didn't actually didn't 0:04:32.760 --> 0:04:35.440 look up that specifically, So so I came up with 0:04:35.680 --> 0:04:38.560 with some tweaking and such a sort of list of 0:04:38.720 --> 0:04:42.200 deaths from external causes that aren't things that basically just 0:04:42.400 --> 0:04:45.559 hit old people like falls. And when you do that list, 0:04:46.080 --> 0:04:50.880 what you get is the counties with the lowest mortality 0:04:51.040 --> 0:04:54.480 rates include a lot of yeah, Brooklyn, the Bronx, a 0:04:54.560 --> 0:04:58.320 bunch of wealthy suburban counties, and definitely New York City 0:04:58.400 --> 0:05:01.160 and the New York Metropolitan Area. You are among the 0:05:01.240 --> 0:05:04.560 safest places in the country overall. The police officer's job 0:05:04.680 --> 0:05:07.720 is not to find out what is the psychological profile, 0:05:08.000 --> 0:05:10.800 what is if the person has the issues at home? 0:05:11.200 --> 0:05:13.760 That's our job as a city. Their job is to 0:05:13.839 --> 0:05:16.640 take dangerous people up the street. My job and the 0:05:16.760 --> 0:05:20.000 job of my agencies is to prevent people from being dangerous. 0:05:20.240 --> 0:05:22.360 What should the mayor be doing. He comes out and 0:05:22.440 --> 0:05:24.480 he gives press conferences, he talks a good game, he 0:05:24.520 --> 0:05:28.080 obviously has good intentions. At the same time, attitudes aren't changing, 0:05:28.120 --> 0:05:30.880 behavior isn't changing, and there's still such a huge question 0:05:30.960 --> 0:05:33.560 mark over remote work and whether it's necessary or not 0:05:33.680 --> 0:05:37.040 to go into the office. And this isn't the answer 0:05:37.120 --> 0:05:39.159 to all of that. I mean, things have been getting 0:05:39.240 --> 0:05:41.159 worse in New York over the past couple of years. 0:05:41.200 --> 0:05:44.640 It looks like the murder wave is fading, but other 0:05:44.800 --> 0:05:48.000 kinds of crimes are up. And so, you know, it's 0:05:48.320 --> 0:05:52.040 someone who felt comfortable coming into New York four years ago, 0:05:52.400 --> 0:05:55.000 it's reasonable that they might feel a little less comfortable now. 0:05:55.440 --> 0:05:57.600 What is just so striking, though, is when you look 0:05:57.640 --> 0:06:00.720 at it and you have this broader view of what 0:06:01.040 --> 0:06:04.520 risk is than just violent crime, you know, and there 0:06:04.560 --> 0:06:07.240 are arguments for and against doing it that way, then 0:06:07.360 --> 0:06:10.000 New York is a really safe place, one of the 0:06:10.080 --> 0:06:14.000 safer places you can be in this country. Some of 0:06:14.400 --> 0:06:17.680 the received wisdom is still true, unfortunately. For example, of 0:06:17.720 --> 0:06:20.160 the city of Baltimore's homicide rate is still a staggering 0:06:20.240 --> 0:06:22.719 fifty eight and a half per one thousand residents. That's 0:06:22.800 --> 0:06:25.000 twice that of Chicago and more than ten times New 0:06:25.080 --> 0:06:27.120 York cities. As you point out, so there are other 0:06:27.200 --> 0:06:30.440 places where it's urban crime is not a myth, and 0:06:30.640 --> 0:06:32.040 you know, crime in New York is not a myth. 0:06:32.160 --> 0:06:36.400 But it's just it's so much lower than in other cities, 0:06:36.520 --> 0:06:38.599 and in a lot of places that aren't big cities, 0:06:38.880 --> 0:06:41.320 And as Justin points out, even the safest areas in 0:06:41.360 --> 0:06:45.159 the US remain killing fields compared with most of Western Europe. 0:06:45.200 --> 0:06:47.560 In Paris, for example, a homicide rate in recent years 0:06:47.839 --> 0:06:51.159 below one per one thousand. Don't forget get in touch 0:06:51.320 --> 0:06:53.520 via Twitter at Vonny Quinn or email v Quinn at 0:06:53.520 --> 0:06:57.560 Bloomberg dot net. Opinions and comments always welcome. So if 0:06:57.600 --> 0:07:00.240 you're not going into the office for whatever reason, you 0:07:00.360 --> 0:07:03.080 might be repeating a pattern from past eras. Let's get 0:07:03.120 --> 0:07:06.279 to University of Georgia history professor and Bloomberg opinion columnist 0:07:06.360 --> 0:07:09.800 Stephen men So, Stephen, telecommuting has obviously been around for 0:07:10.080 --> 0:07:12.960 a long time, but we don't often think about its origins. 0:07:13.360 --> 0:07:15.480 Talk to us a little bit about how it developed 0:07:15.520 --> 0:07:18.960 in the first place. So it goes back to a 0:07:19.080 --> 0:07:23.080 kind of heady period in the sixties when some urban 0:07:23.240 --> 0:07:27.360 planners and theorists of urban life who were concerned about 0:07:27.480 --> 0:07:31.320 traffic congestion, especially in places like Los Angeles, began to 0:07:31.440 --> 0:07:34.800 think about whether it might be possible to substitute communication 0:07:35.120 --> 0:07:38.520 for transportation, in other words, had people to communicate with 0:07:38.600 --> 0:07:42.640 their offices rather than commuting to their offices. It began 0:07:42.760 --> 0:07:46.680 with a couple kind of obscure articles and academic journals, 0:07:46.760 --> 0:07:51.560 as movements oftentimes do, and then in the late nineties 0:07:51.680 --> 0:07:55.640 sixties there was a good illustration of some of these 0:07:55.760 --> 0:07:59.920 concepts that the government sponsored, not because it was trying 0:08:00.040 --> 0:08:02.600 to prove that telecomedian could work, but it was trying 0:08:02.640 --> 0:08:05.520 to do something else, namely, run the space program right. 0:08:05.720 --> 0:08:08.560 And so the system emergence from the Apollo moon landing 0:08:08.640 --> 0:08:11.920 program explained to us what it is right. So the 0:08:12.000 --> 0:08:15.280 Apollo missions were extraordinarily complex, and they linked to all 0:08:15.320 --> 0:08:20.200 of these different contractors and mission control areas and military 0:08:20.320 --> 0:08:23.160 people across the country, and so these people had to 0:08:23.200 --> 0:08:26.120 communicate in real time, and you couldn't just keep flying 0:08:26.200 --> 0:08:29.040 them back and forth across the country. So the several 0:08:29.040 --> 0:08:32.120 government set up these things called Apollo Action Centers, which 0:08:32.160 --> 0:08:36.319 were prototypes of a kind of telecomeeting, meaning that people 0:08:36.360 --> 0:08:39.120 in different parts of the country would gravitate towards their 0:08:39.280 --> 0:08:43.040 local control center and tapped in via this two way 0:08:43.480 --> 0:08:47.199 speaker phone connection that the government set up that worked 0:08:47.240 --> 0:08:51.280 at fifty per second for communicating data, which is one 0:08:52.080 --> 0:08:57.319 of our current upload speed. And after they finished it, 0:08:57.400 --> 0:09:00.200 they did a cost assessment and they realized that they had, say, 0:09:00.360 --> 0:09:03.400 for a dollar, they plowed into this nine dollars and 0:09:03.520 --> 0:09:07.760 travel and salary costs, and so that was pretty dramatic. 0:09:07.960 --> 0:09:10.120 And so one of the people who had worked for 0:09:10.320 --> 0:09:14.479 NASA was this guy Jack Nillis, who was a rocket scientist, 0:09:15.120 --> 0:09:17.880 kind of worked on classified projects. We don't even know 0:09:18.000 --> 0:09:21.199 what he did, honestly, but he went to University of 0:09:21.200 --> 0:09:25.240 Southern California, which was of course traffic congestion central, and 0:09:25.800 --> 0:09:28.200 it was there that he took command of a team 0:09:28.280 --> 0:09:30.280 of people who wanted to figure out if there were 0:09:30.280 --> 0:09:32.599 a way to kind of implement some version of this 0:09:32.800 --> 0:09:36.720 for civilians, and they came up with this pilot program 0:09:36.880 --> 0:09:39.360 with an insurance company where they did the exact same thing, 0:09:39.440 --> 0:09:42.360 but in l A it wasn't people working from home. 0:09:42.440 --> 0:09:46.199 It was people coming to like the nearest node and 0:09:46.280 --> 0:09:50.880 they would commute in to the central office, but over 0:09:51.040 --> 0:09:55.280 phone lines and eventually computer lines, because it was at 0:09:55.320 --> 0:09:58.199 that moment that all of this technology, computer networks like 0:09:58.520 --> 0:10:02.160 arponnet to, the technology came online. Right, And if you 0:10:02.200 --> 0:10:04.640 would ask me, I probably would have mumbled something about 0:10:04.640 --> 0:10:07.760 telephone networks or as you said, the diminishing size of computers, 0:10:07.920 --> 0:10:10.920 or maybe even the rise of skyscrapers and inner city living. 0:10:11.280 --> 0:10:14.719 But in actual fact, when it really took hold was 0:10:14.840 --> 0:10:17.120 in response to the OPEC oil embargo, as you point 0:10:17.160 --> 0:10:20.280 out in nineteen three, right, And so these guys were 0:10:20.360 --> 0:10:23.360 doing this project and all of a sudden, everyone wants 0:10:23.400 --> 0:10:26.320 to save money on gasoline, and there they are. They've 0:10:26.360 --> 0:10:29.040 got a solution, you know, like don't go into the office. 0:10:29.480 --> 0:10:32.280 That was the first iteration of teleco meeting was a 0:10:32.440 --> 0:10:35.520 kind of dispersal of the workforce as opposed to like 0:10:35.720 --> 0:10:39.240 total diffusion where everyone's working from their home. Now, I'm 0:10:39.320 --> 0:10:42.360 curious unions were a lot stronger back in the day 0:10:42.440 --> 0:10:44.880 and more prevalent in the workplace then, So how did 0:10:45.080 --> 0:10:48.199 unions react. Was this something that they reacted to positively 0:10:48.400 --> 0:10:52.600 or negatively? Rather negatively, As soon as telecom meeting became chicked, 0:10:52.640 --> 0:10:55.599 around in policy circles, unions like the A f l C. 0:10:55.760 --> 0:10:58.440 I Oh said, well, you know, wait a second, there's 0:10:58.480 --> 0:11:00.800 some peril here, because how are you gonna force workplace 0:11:00.840 --> 0:11:04.160 safety at home? You know, when someone trips over the 0:11:04.240 --> 0:11:08.240 extension cord, are they on on the company's workmen's comp 0:11:08.559 --> 0:11:10.720 are they Is it just their faults? So there are 0:11:10.720 --> 0:11:14.600 all these things that they criticized, but the real criticism actually, 0:11:14.760 --> 0:11:19.640 interestingly came eventually from an unlikely source, which was management. 0:11:20.720 --> 0:11:25.920 How is that unlikely? Well? True, Well, you think about management. 0:11:26.120 --> 0:11:28.559 If given an opportunity to stay money, they would take 0:11:28.600 --> 0:11:32.000 it right. But the idea of letting their employees work 0:11:32.040 --> 0:11:35.760 off site, that was worrisome. But that didn't stop a 0:11:35.840 --> 0:11:39.480 lot of futurists in the late seventies, people like Alvin Toffler, 0:11:39.720 --> 0:11:42.960 from counting the vision that we would by the end 0:11:43.000 --> 0:11:45.599 of the nineteen eighties all be working at home and 0:11:45.760 --> 0:11:49.600 what he called our electronic cottages. We all electronic cottages. 0:11:49.640 --> 0:11:52.199 I like that. What, though, did we find out conclusively 0:11:52.240 --> 0:11:56.559 about productivity and expense reduction? That's an excellent question and 0:11:56.760 --> 0:11:59.160 one that it depends on who you talked to. The 0:11:59.280 --> 0:12:03.080 early research church and much of the later research suggested 0:12:03.240 --> 0:12:07.360 that in fact, there were productivity gains for that pool 0:12:07.520 --> 0:12:12.520 of employees that was somewhat self selecting who worked from home. So, 0:12:12.640 --> 0:12:15.480 in other words, in the seventies and eighties and even 0:12:15.600 --> 0:12:19.400 well into the outs the pandemic, though, case studies that 0:12:19.440 --> 0:12:22.240 are coming out of that suggests something else happened, which 0:12:22.320 --> 0:12:25.960 is the productivity actually went down and that there were 0:12:26.040 --> 0:12:30.920 other problems with cohesion of workforces. This is probably easier 0:12:30.960 --> 0:12:34.000 to square than it sounds, namely that like, if three 0:12:34.080 --> 0:12:36.640 percent of your workforce is working off site and they're 0:12:36.720 --> 0:12:39.559 really well suited for that kind of work, fine, But 0:12:39.640 --> 0:12:41.920 when you take everyone and send them home to their 0:12:41.960 --> 0:12:46.720 electronic cottages, to Toffler's phrase, a lot of them are 0:12:46.800 --> 0:12:49.680 trying to contend with everything from like walking the dog, 0:12:50.040 --> 0:12:54.760 caring for toddlers, to doing everything else that they really 0:12:54.760 --> 0:12:57.079 would prefer not to be doing while they work and 0:12:57.200 --> 0:13:00.280 previously had divided. So there may be ways in which 0:13:00.400 --> 0:13:04.760 these two experiments, the experiments of early telecommunititting and the 0:13:04.880 --> 0:13:08.199 pandemic experiment, are really apples and orange in terms of 0:13:09.640 --> 0:13:13.079 well the other thing, And these are very much ongoing investigations. 0:13:13.280 --> 0:13:15.840 How much did cities and do cities and their planners 0:13:15.920 --> 0:13:19.079 have a say in the remote versus in office workplace debate. 0:13:19.160 --> 0:13:21.520 That would seem like they would want to have a say. 0:13:21.679 --> 0:13:25.199 And obviously some cities are very much suffering post pandemic 0:13:25.280 --> 0:13:28.480 because of remote work. Other cities are thriving. Is there 0:13:28.480 --> 0:13:31.400 a conclusion on that. There isn't a conclusion, But you're 0:13:31.400 --> 0:13:35.000 absolutely right that for urban planners this is extraordinarily disruptive 0:13:35.240 --> 0:13:38.680 because there are ways in which obviously this hurts central 0:13:38.760 --> 0:13:41.640 business districts if people ceased to come in at the 0:13:41.720 --> 0:13:44.439 same time, though it could also create massive demand for 0:13:44.600 --> 0:13:49.040 services in more decentralized, scattered nodes. So it's there are 0:13:49.080 --> 0:13:51.920 ways this could play out that are really kind of 0:13:52.040 --> 0:13:55.920 in many cases, perhaps even counterintuitive. So, for example, we 0:13:56.040 --> 0:14:01.240 think of how telecommuting limits traffic congestion. The flip side 0:14:01.280 --> 0:14:04.439 of that is, if everyone can go anywhere at any time, 0:14:05.200 --> 0:14:09.040 you're also maybe putting a kind of constant lower level 0:14:09.080 --> 0:14:12.760 of congestion on the traffic rid at all times, and 0:14:12.840 --> 0:14:15.439 that could in a way be very disruptive in its 0:14:15.440 --> 0:14:18.480 own right and hard to plan for. Just on all 0:14:18.520 --> 0:14:20.200 of this, thinking back to the competition for the new 0:14:20.240 --> 0:14:23.320 Amazon headquarters, it almost seems quaint. It almost seems like 0:14:23.360 --> 0:14:25.520 a waste of resources for local governments to be doing 0:14:25.560 --> 0:14:28.920 things like offering incentives in an era of remote work. 0:14:29.200 --> 0:14:31.600 Yeah no, because think about it in terms of what 0:14:31.720 --> 0:14:34.240 if the jobs that you're bringing here are being performed 0:14:34.320 --> 0:14:36.040 by people like you bring them here, and then they 0:14:36.120 --> 0:14:39.480 end up being performed by people in another stage. There 0:14:39.520 --> 0:14:41.560 are all sorts of ways in which this messages with 0:14:41.760 --> 0:14:44.240 a lot of the usual incentive structures that we think 0:14:44.240 --> 0:14:47.360 about when it comes to cities and attracting economic growth. 0:14:47.840 --> 0:14:51.720 Stephen Mims There, So you're working from anywhere and you're 0:14:51.760 --> 0:14:55.520 making a quarter of a million dollars, sounds perfect right, Well, 0:14:55.560 --> 0:14:58.760 Alexis Leander's dug into some data which show more than 0:14:58.800 --> 0:15:02.520 a third of you are that paycheck to paycheck sounds startling. Well, 0:15:02.800 --> 0:15:05.720 let's hear more from Alexis herself. So, Alexis, how on 0:15:05.920 --> 0:15:08.040 earth can you be making a quarter of a million 0:15:08.080 --> 0:15:10.840 dollars a year and still be living paycheck to paycheck? 0:15:11.920 --> 0:15:14.640 I know it sounds absurd. I mean, you know, just 0:15:14.760 --> 0:15:17.360 to put it in perspective, two hundred fifty thousand dollars 0:15:17.480 --> 0:15:20.360 is almost four times the media and US salary and 0:15:20.720 --> 0:15:23.920 put those earners in the time top five percent of 0:15:24.000 --> 0:15:27.840 all earners in America. So to hear so many according 0:15:27.880 --> 0:15:30.240 to this survey that I highlighted in my column, one 0:15:30.320 --> 0:15:33.240 third of them, more than one thirty six percent of 0:15:33.280 --> 0:15:36.200 them say that even with that kind of income, they're 0:15:36.280 --> 0:15:38.880 basically spending everything they make each month and living quote 0:15:38.960 --> 0:15:42.280 unquote paycheck to paycheck is very unnerving. Does this have 0:15:42.400 --> 0:15:45.280 anything to do with the pandemic working from home large 0:15:45.320 --> 0:15:48.040 item expenses perhaps, or or perhaps people were eating out 0:15:48.200 --> 0:15:50.040 or getting take out more because they potentially had a 0:15:50.080 --> 0:15:52.760 more flexible schedule. That's a good question. I don't know 0:15:52.800 --> 0:15:54.480 if it's so much without remote work, but I do 0:15:54.600 --> 0:15:57.640 think housing is one of the big culprits. I think 0:15:57.720 --> 0:16:00.840 with housing, we've seen mortgage rape sky rocket, We've seen 0:16:00.880 --> 0:16:04.320 home prices appreciate so incredibly much. So I think when 0:16:04.360 --> 0:16:06.640 you take those two things together, and especially for this 0:16:06.800 --> 0:16:10.000 high income group, they tend to probably leverage themselves. And 0:16:10.160 --> 0:16:12.440 because of that, I think housing is one of the 0:16:12.520 --> 0:16:16.360 reasons folks and missed cohort are feeling so stretched. Is 0:16:16.400 --> 0:16:17.520 there a need to put in a bit of a 0:16:17.560 --> 0:16:20.080 caveat that this might be a bit of an inflation 0:16:20.200 --> 0:16:22.800 story as well. Are we definitely seeing the impact of 0:16:22.880 --> 0:16:25.800 inflation on these salary earners? Definitely, And I think it 0:16:25.840 --> 0:16:28.240 ties into what you've said before, which is we're also 0:16:28.280 --> 0:16:30.520 seeing people who because they were home, you know, at 0:16:30.600 --> 0:16:33.080 this level, they're starting to travel more, they're starting to 0:16:33.120 --> 0:16:35.080 eat out, they're starting to do more things. So all 0:16:35.160 --> 0:16:37.360 of these things are kind of happening at the same time. 0:16:37.880 --> 0:16:39.800 And right now they've been lucky enough to have their 0:16:39.840 --> 0:16:42.400 student loan payment on hold, um, but that's going to 0:16:42.560 --> 0:16:44.920 change soon. So that's something really people have to start 0:16:45.000 --> 0:16:47.760 thinking about and budgeting for. That was really eye opening. 0:16:47.840 --> 0:16:50.320 So hundreds of dollars a month that would have been 0:16:50.360 --> 0:16:54.640 potentially coming out of that salary is on moratorium because 0:16:54.680 --> 0:16:57.640 they're taking advantage of the student loan repayment moratorium. So 0:16:57.920 --> 0:17:00.360 what happens when that takes back in again, ssuming it 0:17:00.440 --> 0:17:02.640 does right? Right? I mean, student loan debt for this 0:17:02.880 --> 0:17:05.360 for this crowd is a very big deal. Um. More 0:17:05.400 --> 0:17:08.800 than of total federal student loan debt is held by 0:17:08.840 --> 0:17:11.480 households with incomes from about a hundred thousand dollars to 0:17:11.560 --> 0:17:14.119 three hundred seventy five thousand dollars and that's the largest 0:17:14.119 --> 0:17:17.080 percentage of any income group. So so many high earners 0:17:17.160 --> 0:17:20.840 have professional or doctorate degrees. So if you're an average 0:17:21.280 --> 0:17:24.000 student or your you went to graduate school, and if 0:17:24.040 --> 0:17:27.200 you take your undergraduate loans coupled with your graduate student loans, 0:17:27.640 --> 0:17:30.199 you could be looking at total debt is more than 0:17:30.240 --> 0:17:33.239 eighty two thousand dollars. That means monthly payments about nine 0:17:33.680 --> 0:17:35.560 fifty dollars a month has been on hold for almost 0:17:35.600 --> 0:17:39.159 thirty months, which is terrifying given that rents are going 0:17:39.240 --> 0:17:41.840 up in big cities as well as this potentially coming 0:17:41.880 --> 0:17:45.120 back into play for these people. I mean, it's terrifying 0:17:45.400 --> 0:17:47.119 within reason. We're talking about people who are in a 0:17:47.200 --> 0:17:50.680 quarter of a million dollars here, so let's be too concerned. 0:17:51.000 --> 0:17:53.560 But you do have to wonder if they're making four 0:17:53.640 --> 0:17:56.000 times the median wage in the United States, what are 0:17:56.080 --> 0:17:59.320 those earning less than that doing to finance their lives? 0:18:00.400 --> 0:18:02.760 Exactly right, exactly right. I mean I think the big 0:18:02.800 --> 0:18:07.040 difference again is mortgage, so homeownership versus renting. A lot 0:18:07.080 --> 0:18:09.399 of people who are making less money, they don't have 0:18:09.480 --> 0:18:11.320 to deal with rising mortgage costs, but they do have 0:18:11.400 --> 0:18:14.000 to deal with rising rents. So that's obviously something that 0:18:14.119 --> 0:18:16.320 has to be factored into it. And I just want 0:18:16.359 --> 0:18:19.120 to point out one key detail of this group. These 0:18:19.160 --> 0:18:21.400 people who are making at least two hundred fifty thousand dollars, 0:18:21.520 --> 0:18:24.720 who say they're living paycheck to paycheck. They're able to 0:18:24.920 --> 0:18:27.240 still pay their bills, but the bills that they're paying 0:18:27.359 --> 0:18:31.800 include automated savings for things like retirement in college plans. 0:18:31.880 --> 0:18:34.040 So it is really important when at least when I 0:18:34.119 --> 0:18:36.760 think of paycheck to paycheck, to me, that's someone who 0:18:36.800 --> 0:18:40.840 whatever they're earning, they're spending basically on housing food. These people, 0:18:40.960 --> 0:18:43.320 that's not necessarily the case. They are doing things that 0:18:43.440 --> 0:18:46.200 ultimately will help them in retirement or their kids college 0:18:46.240 --> 0:18:48.520 plans down the line, and that is a huge covey 0:18:48.560 --> 0:18:52.439 out because those are things that catch lower income earners 0:18:52.560 --> 0:18:55.720 out later on in life, and it's very difficult. The 0:18:55.800 --> 0:18:57.639 other thing that I wanted to point out here is 0:18:57.840 --> 0:19:02.480 revolving loans credit card dead These people not necessarily suffering 0:19:02.880 --> 0:19:04.800 late fees or anything like that, because they do tend 0:19:04.840 --> 0:19:06.640 to pay off any credit card debt that they incur 0:19:07.359 --> 0:19:10.200 exactly right. That was kind of surprising to me because 0:19:10.600 --> 0:19:12.840 you would think if you're living paycheck to paycheck. And 0:19:12.960 --> 0:19:15.160 even among this cohort, there are those who are living 0:19:15.160 --> 0:19:17.600 paycheck to paycheck and aren't even able to pay all 0:19:17.640 --> 0:19:19.880 of their bills. So you would think someone be turning 0:19:19.920 --> 0:19:23.040 to credit cards. But according to a survey by payments 0:19:23.080 --> 0:19:25.560 dot Com and the Lending Club, for those who say 0:19:25.560 --> 0:19:27.800 they're earning at least two hundred fifty thousand dollars and 0:19:27.840 --> 0:19:31.120 are living paycheck to paycheck, six of them are saying 0:19:31.440 --> 0:19:33.880 they're not revolving a balance, so they're paying off their 0:19:33.920 --> 0:19:36.960 credit card balances in full every month. That said, though, 0:19:37.000 --> 0:19:39.520 there was a said report recently that said the end 0:19:39.600 --> 0:19:42.159 of student loan forbearance could lead to a deterioration and 0:19:42.240 --> 0:19:45.439 credit risk profiles for borrowers. It didn't look at specific 0:19:45.520 --> 0:19:48.399 income levels, but again it's just worth raising. So far, 0:19:48.520 --> 0:19:50.480 this group doesn't seem to be turning to credit cards 0:19:50.600 --> 0:19:53.240 to plug the gap, but will that continue once these 0:19:53.240 --> 0:19:55.960 student owned payments get turned back on Alexos? Was there 0:19:56.040 --> 0:19:58.920 any question asked about what happens if we do see 0:19:58.960 --> 0:20:01.600 a recession or if we start to see unemployment go 0:20:02.080 --> 0:20:04.240 up once again. So we're in a very tight labor 0:20:04.320 --> 0:20:08.640 market and a very labor friendly labor market. That's that's 0:20:08.640 --> 0:20:11.119 a great point that right now, it still seems like 0:20:11.200 --> 0:20:13.920 despite what consumers, especially at the higher end, maybe saying 0:20:14.280 --> 0:20:17.840 about being pessimistic with respect to their finances, they're still spending. 0:20:17.960 --> 0:20:19.840 You know, maybe they've rained in, they're spending a month, 0:20:19.880 --> 0:20:22.520 but they're still spending a bit above average. Once that 0:20:22.680 --> 0:20:24.840 starts to turn, and especially if we start to see 0:20:24.920 --> 0:20:27.840 some labor market changes, that's I think one will start 0:20:27.880 --> 0:20:30.000 to get worried, and you know, then maybe those credit 0:20:30.040 --> 0:20:33.240 card dances will start to go up. Alexis Leanders do 0:20:33.359 --> 0:20:36.160 get in touch with comments and opinions. I'm at Vonnie 0:20:36.240 --> 0:20:39.080 Quinn on Twitter or email v Quinn at Bloomberg dot net. 0:20:39.480 --> 0:20:42.240 Stanley drucken Miller told investors at the sone conference this 0:20:42.359 --> 0:20:45.240 week where maybe six months into a bear market and 0:20:45.320 --> 0:20:48.439 predicting a soft landing means going against decades of history. 0:20:48.920 --> 0:20:52.840 Yet more people are seeing the possibility, including Pimco's Tony Krisenzi. 0:20:53.040 --> 0:20:55.320 It does seem like the odds of a soft landing 0:20:55.520 --> 0:20:59.159 are reasonably good, but it's tough to manage what the 0:20:59.200 --> 0:21:02.640 federal reserve, of course, is to avoid an outright recession. 0:21:02.680 --> 0:21:04.800 I had a chat with John Authors, who's been warning 0:21:04.880 --> 0:21:07.080