1 00:00:10,039 --> 00:00:13,840 Speaker 1: Hello, and welcome to another episode of the Odd Lots Podcast. 2 00:00:13,880 --> 00:00:18,400 Speaker 1: I'm Joe Wisenthal and I'm Tracy Halloway. Tracy last month's 3 00:00:18,520 --> 00:00:21,360 Speaker 1: inflation number, and I guess it was just a disappointment, right, 4 00:00:21,360 --> 00:00:24,360 Speaker 1: because two months ago it was this cool number both 5 00:00:24,400 --> 00:00:27,760 Speaker 1: on headline core, like maybe the turn is finally here, 6 00:00:28,360 --> 00:00:30,720 Speaker 1: and then last month it was like, no, straight back 7 00:00:30,760 --> 00:00:33,000 Speaker 1: up again. How many words did you write about why 8 00:00:33,040 --> 00:00:35,199 Speaker 1: people should be focused on month on month versus year 9 00:00:35,240 --> 00:00:39,080 Speaker 1: on here? I still think that from an investor or 10 00:00:39,120 --> 00:00:41,440 Speaker 1: standpoint or just someone trying to understand you account clearly 11 00:00:41,479 --> 00:00:45,480 Speaker 1: like the sequential numbers are more telling. I wasn't, Tracy. 12 00:00:45,640 --> 00:00:48,840 Speaker 1: I resent the insinuation that you think I would write, 13 00:00:48,840 --> 00:00:52,360 Speaker 1: so I would never insinuate anything, Okay, but you're right, Okay, 14 00:00:52,520 --> 00:00:56,440 Speaker 1: So people were expecting inflation to start to slow down 15 00:00:56,600 --> 00:00:58,280 Speaker 1: a little bit, and that's why there was lots of 16 00:00:58,320 --> 00:01:00,200 Speaker 1: talk about why you should look at the sequence whole 17 00:01:00,280 --> 00:01:03,360 Speaker 1: month on month data versus the year on year. But 18 00:01:03,600 --> 00:01:06,280 Speaker 1: what we saw instead was basically, any way you slice 19 00:01:06,319 --> 00:01:10,480 Speaker 1: the data, it looked disappointing. And where you going to 20 00:01:10,560 --> 00:01:12,800 Speaker 1: defend month on month again? No, no, of course, I 21 00:01:12,920 --> 00:01:16,720 Speaker 1: was just gonna say, ironically, the one the only measure 22 00:01:16,800 --> 00:01:20,680 Speaker 1: that looked good was the completely unsliced headline data because 23 00:01:20,720 --> 00:01:23,640 Speaker 1: that was so far dragged out, but the moment you 24 00:01:23,680 --> 00:01:26,120 Speaker 1: did even the slightest bit of product under headline was like, 25 00:01:26,160 --> 00:01:29,039 Speaker 1: oh my god, raging hut. All right. Well, the I 26 00:01:29,080 --> 00:01:31,760 Speaker 1: think the big takeaway from that number, other than it 27 00:01:31,840 --> 00:01:34,200 Speaker 1: being disappointing, was the fact that we really see some 28 00:01:34,240 --> 00:01:37,240 Speaker 1: of these price increases starting to spread from things like 29 00:01:37,280 --> 00:01:41,240 Speaker 1: food and energy and more towards services. And services, as 30 00:01:41,319 --> 00:01:43,880 Speaker 1: everyone is now finding out, is a big, big part 31 00:01:43,920 --> 00:01:46,120 Speaker 1: of the core index. And I guess everyone called this 32 00:01:46,200 --> 00:01:47,760 Speaker 1: to like, I think last year they're like, oh, we're 33 00:01:47,760 --> 00:01:50,240 Speaker 1: gonna have this big shift to services and yeah, sure, 34 00:01:50,280 --> 00:01:53,200 Speaker 1: good prices will come down and bull whip effects and 35 00:01:53,320 --> 00:01:56,880 Speaker 1: inventories and all that. But now it's here and it's like, 36 00:01:56,880 --> 00:01:58,280 Speaker 1: oh man, this could be here for a while and 37 00:01:58,280 --> 00:02:00,200 Speaker 1: it's not slowing down yet. Yeah, And I think the 38 00:02:00,200 --> 00:02:02,240 Speaker 1: big question is how long does it take to feed 39 00:02:02,240 --> 00:02:04,000 Speaker 1: into the index and how long does it take to 40 00:02:04,200 --> 00:02:07,600 Speaker 1: kind of go away? And there are different data points, 41 00:02:07,680 --> 00:02:09,520 Speaker 1: and there's been some discussion of this as well. There's 42 00:02:09,560 --> 00:02:12,880 Speaker 1: private market data points, for instance, that show rents are 43 00:02:12,960 --> 00:02:16,639 Speaker 1: starting to slow, so when does that feed into CPI? Right, So, 44 00:02:16,800 --> 00:02:19,760 Speaker 1: various online companies like a Zillo or something, they'll have 45 00:02:19,760 --> 00:02:21,680 Speaker 1: a rent index. And this sort of gets to the 46 00:02:21,760 --> 00:02:24,080 Speaker 1: question because, first of all, the thing that one of 47 00:02:24,080 --> 00:02:26,919 Speaker 1: the big upward drivers of inflation and the last report 48 00:02:27,200 --> 00:02:29,440 Speaker 1: was rent. Everyone most people feel rent. It's like a 49 00:02:29,520 --> 00:02:32,560 Speaker 1: very salient category. There are some categories that maybe are 50 00:02:32,560 --> 00:02:35,520 Speaker 1: more hidden. Rent is not one of them. Shelter is 51 00:02:35,520 --> 00:02:37,799 Speaker 1: not one of them. But then yes, there is this thing. 52 00:02:37,840 --> 00:02:40,120 Speaker 1: So it's like, Okay, we have these private measures that 53 00:02:40,280 --> 00:02:42,320 Speaker 1: seem to be rolling over a little bit, but the 54 00:02:42,360 --> 00:02:44,600 Speaker 1: numbers in the CPI keep going up. So is this 55 00:02:44,639 --> 00:02:47,079 Speaker 1: the case where the CPI is just lagged like bad 56 00:02:47,200 --> 00:02:50,959 Speaker 1: data or is it people are misunderstanding the relationship between 57 00:02:50,960 --> 00:02:53,720 Speaker 1: the official government numbers and what some of these private 58 00:02:53,720 --> 00:02:57,680 Speaker 1: surveys are ship Today we're going to be digging deep 59 00:02:57,800 --> 00:03:01,360 Speaker 1: into those numbers, right, absolutely, So let's get right to it. 60 00:03:01,560 --> 00:03:05,880 Speaker 1: We have the ultimate guest for digging into inflation numbers, 61 00:03:05,919 --> 00:03:08,079 Speaker 1: and he knows more about like what these numbers actually 62 00:03:08,120 --> 00:03:10,639 Speaker 1: mean and how they're derived. I think you've talked to 63 00:03:10,680 --> 00:03:13,640 Speaker 1: him several times, and you're reporting on like the minutia 64 00:03:13,960 --> 00:03:17,639 Speaker 1: like you when you did like mayonnaise reporting, It's like, Okay, 65 00:03:17,639 --> 00:03:19,799 Speaker 1: where is this in which index? And how much of 66 00:03:19,919 --> 00:03:24,120 Speaker 1: this is like soy oils versus condiments? Like he knows everything. 67 00:03:24,320 --> 00:03:27,400 Speaker 1: The way we measure inflation never ceases to amaze me. 68 00:03:27,480 --> 00:03:29,400 Speaker 1: And there's just so much to say about the actual 69 00:03:29,440 --> 00:03:32,400 Speaker 1: construction of the indicries and things that people don't normally 70 00:03:32,440 --> 00:03:35,240 Speaker 1: talk about but we probably should. Let's talk about them. 71 00:03:35,240 --> 00:03:37,720 Speaker 1: We're gonna be bringing back to the show a past guest. 72 00:03:37,760 --> 00:03:41,880 Speaker 1: O'mar Sharif is the president and founder of Inflation Insights, 73 00:03:41,960 --> 00:03:44,080 Speaker 1: and he will answer all our questions about why some 74 00:03:44,400 --> 00:03:46,960 Speaker 1: numbers are going up maybe some hopefully that go down. 75 00:03:46,960 --> 00:03:48,720 Speaker 1: So Ama, thank you so much for coming back on 76 00:03:48,760 --> 00:03:51,720 Speaker 1: the show. What's going on? When is the numbers going 77 00:03:51,800 --> 00:03:54,480 Speaker 1: to start turning down? This is I thought inflation was transitor. 78 00:03:54,680 --> 00:03:56,360 Speaker 1: I made a whole like you know, I was like 79 00:03:56,480 --> 00:03:58,880 Speaker 1: I was like on team Transitory. Now I look ridiculous. 80 00:03:59,720 --> 00:04:03,520 Speaker 1: Um well, I think probably you know the turn of 81 00:04:03,560 --> 00:04:06,360 Speaker 1: this year is because what I'm thinking is we're gonna 82 00:04:06,400 --> 00:04:09,600 Speaker 1: start to see the monthly rate, especially the core, start 83 00:04:09,680 --> 00:04:11,080 Speaker 1: to really kind of come off. I mean, we've been 84 00:04:11,120 --> 00:04:13,280 Speaker 1: kind of stuck around point flat point six every month 85 00:04:13,280 --> 00:04:15,720 Speaker 1: on the core pretty much for close to a year. Um, 86 00:04:15,960 --> 00:04:17,919 Speaker 1: we haven't got a long relief, but I think that 87 00:04:17,960 --> 00:04:20,520 Speaker 1: relief is coming from a few different areas, hopefully in 88 00:04:20,520 --> 00:04:22,919 Speaker 1: the next couple of months. Okay, I'm gonna clip. It 89 00:04:22,920 --> 00:04:24,760 Speaker 1: doesn't matter how long it takes. I'm going to claim 90 00:04:24,839 --> 00:04:29,560 Speaker 1: victory in five years of inflation comes down. Great. Um, okay, well, 91 00:04:29,600 --> 00:04:31,680 Speaker 1: maybe we can talk about one of the things that 92 00:04:31,720 --> 00:04:35,479 Speaker 1: people expected to start coming down and it hasn't, at 93 00:04:35,560 --> 00:04:38,760 Speaker 1: least according to um last month's data, and that's used cars. 94 00:04:38,960 --> 00:04:41,160 Speaker 1: Car prices, and this was one of the big drivers 95 00:04:41,160 --> 00:04:43,760 Speaker 1: of inflation actually, you know, going up over the past 96 00:04:43,839 --> 00:04:46,600 Speaker 1: year or so. Why haven't prices come down? This is 97 00:04:46,640 --> 00:04:49,560 Speaker 1: what everyone was expecting to happen. Yeah, so use car 98 00:04:49,640 --> 00:04:52,240 Speaker 1: prices like a lot of things. Uh, you know, when 99 00:04:52,279 --> 00:04:55,120 Speaker 1: prices cool sale prices are going up, they are just 100 00:04:55,440 --> 00:04:57,960 Speaker 1: very quickly on the way up. When they are coming down, 101 00:04:58,040 --> 00:05:00,159 Speaker 1: they take a little hell to come down. And so 102 00:05:00,600 --> 00:05:03,080 Speaker 1: what we've seen, honestly all year long is that wholesale 103 00:05:03,120 --> 00:05:05,200 Speaker 1: prices are down very, very sharply. You want to look 104 00:05:05,240 --> 00:05:08,560 Speaker 1: at Manheim Black Book data and JD Power, which is 105 00:05:08,680 --> 00:05:11,760 Speaker 1: sourced data. Actually for the BLS um all of these 106 00:05:11,760 --> 00:05:13,679 Speaker 1: things that are down, you have ten and eleven twelve 107 00:05:13,760 --> 00:05:16,880 Speaker 1: percent depending on the indext over the last six seven months. 108 00:05:17,480 --> 00:05:19,839 Speaker 1: Retail litt on the other hand, has been kind of 109 00:05:20,040 --> 00:05:23,000 Speaker 1: roughly flat because a lot of sellers are not really 110 00:05:23,000 --> 00:05:26,080 Speaker 1: pulling down the crisis. But we're starting to see that change, 111 00:05:26,080 --> 00:05:27,520 Speaker 1: and really over the last six or seven weeks, I 112 00:05:27,520 --> 00:05:30,560 Speaker 1: would say that that is starting to adjust. So model years, 113 00:05:30,600 --> 00:05:32,280 Speaker 1: you know, two year old models, three row models for 114 00:05:32,440 --> 00:05:34,800 Speaker 1: those prices and retail prices are coming down. You can 115 00:05:34,800 --> 00:05:37,200 Speaker 1: see this in the BlackBook Retail Index, for example, prices 116 00:05:37,279 --> 00:05:39,280 Speaker 1: were down about two and a half percent in August. 117 00:05:39,600 --> 00:05:42,240 Speaker 1: So all we're really waiting to see is that data 118 00:05:42,600 --> 00:05:45,559 Speaker 1: translate into the CPI and the next we use cars 119 00:05:45,560 --> 00:05:47,800 Speaker 1: and I think, you know, September it is a good 120 00:05:47,800 --> 00:05:49,960 Speaker 1: point where that might enter, but I think October is 121 00:05:49,960 --> 00:05:53,080 Speaker 1: probably the month you really want to focus on. September. 122 00:05:53,120 --> 00:05:55,680 Speaker 1: There's a lot of adjustments that are happening in September, 123 00:05:56,120 --> 00:05:58,800 Speaker 1: but September October, I think is when you really are 124 00:05:58,800 --> 00:06:01,360 Speaker 1: going to start to see the retail stuff on these 125 00:06:01,400 --> 00:06:03,400 Speaker 1: cars in next start to come come off in the 126 00:06:03,400 --> 00:06:05,159 Speaker 1: CPI and that that's going to be a big boon 127 00:06:05,240 --> 00:06:07,920 Speaker 1: in terms of you know, getting that core weight quarter 128 00:06:08,000 --> 00:06:10,799 Speaker 1: and next lower. How do you actually go about, because 129 00:06:10,800 --> 00:06:12,479 Speaker 1: this is your day to day business, how do you 130 00:06:12,520 --> 00:06:16,120 Speaker 1: go about trying to measure that lag between you know, 131 00:06:16,160 --> 00:06:19,159 Speaker 1: what we see in the market and what we actually 132 00:06:19,200 --> 00:06:21,720 Speaker 1: see showing up in the CPI data. First of all, 133 00:06:21,760 --> 00:06:24,400 Speaker 1: you're looking at these market industries, you know, whether it's 134 00:06:24,440 --> 00:06:27,800 Speaker 1: span Him or Black Book, and you're essentially mapping them 135 00:06:27,920 --> 00:06:31,279 Speaker 1: is at the wholesale level against the retail price index 136 00:06:31,400 --> 00:06:35,520 Speaker 1: for the CPI UM. Now, obviously wholesale, you know, typically 137 00:06:35,720 --> 00:06:39,679 Speaker 1: defined as the strongest correlations, will be with wholesale changes 138 00:06:40,320 --> 00:06:43,320 Speaker 1: feeding roughly about two months later into the CPI. Now 139 00:06:43,360 --> 00:06:45,960 Speaker 1: what's really interesting is like before the pandemic, this was 140 00:06:46,240 --> 00:06:49,040 Speaker 1: pretty much a constant roughly a two month lag, so 141 00:06:49,080 --> 00:06:51,840 Speaker 1: eight weeks later, whatever happened wholesale typically showed up in 142 00:06:51,880 --> 00:06:54,960 Speaker 1: the CPI. What the pandemic did was completely throw these 143 00:06:55,040 --> 00:06:57,839 Speaker 1: lags off to the point where you know, prices started 144 00:06:57,880 --> 00:07:01,279 Speaker 1: moving at the wholesale level, obviously they're going up, and 145 00:07:01,320 --> 00:07:04,880 Speaker 1: that immediately fed into retail like there was no lag whatsoever, 146 00:07:05,360 --> 00:07:07,960 Speaker 1: and if you're one of five six percent of wholesale 147 00:07:08,000 --> 00:07:10,240 Speaker 1: one month, guess what the CPI was going up five 148 00:07:10,520 --> 00:07:12,960 Speaker 1: pc and use cars the next one. Now, what we're 149 00:07:13,000 --> 00:07:15,120 Speaker 1: seeing now, I think is a little bit of a 150 00:07:15,120 --> 00:07:18,160 Speaker 1: reversion to that, um, you know, the old lag of 151 00:07:18,160 --> 00:07:20,200 Speaker 1: about to shoot three months. And that's why I think. 152 00:07:20,800 --> 00:07:23,200 Speaker 1: You know, we've seen wholesale come off the last several months, 153 00:07:23,200 --> 00:07:24,640 Speaker 1: and people are saying, we wait, it's like on the 154 00:07:24,680 --> 00:07:28,240 Speaker 1: CPI use cars index is you know, kind of unchanged 155 00:07:28,320 --> 00:07:30,840 Speaker 1: or maybe up a little bit. So I think it's 156 00:07:30,840 --> 00:07:32,560 Speaker 1: it's just the issues that the lags are are kind 157 00:07:32,560 --> 00:07:34,240 Speaker 1: of back to what they were. This is sort of 158 00:07:34,240 --> 00:07:36,240 Speaker 1: like gasolute. You know, when gasing prices go up and 159 00:07:36,280 --> 00:07:38,680 Speaker 1: wholesale level you feel it right away, and you see 160 00:07:38,680 --> 00:07:40,640 Speaker 1: it right away at the pub when they go down, 161 00:07:40,760 --> 00:07:44,560 Speaker 1: it's a very gradual decline, right you're kind of pocketing 162 00:07:44,560 --> 00:07:47,120 Speaker 1: that extra margin. And I think dealers are doing the 163 00:07:47,160 --> 00:07:49,680 Speaker 1: same thing and happened for a while. But I think 164 00:07:49,720 --> 00:07:51,560 Speaker 1: that jig is up and should be over the next 165 00:07:51,600 --> 00:07:54,560 Speaker 1: couple of months. So let's talk a little bit more 166 00:07:54,600 --> 00:07:56,520 Speaker 1: about this. And you know, I'm starting to like feel 167 00:07:56,520 --> 00:07:59,400 Speaker 1: a little bit better about always big wrong on everything 168 00:07:59,400 --> 00:08:01,800 Speaker 1: because I just got these measures, right, I look at trucking, 169 00:08:02,000 --> 00:08:05,080 Speaker 1: look at cars, I look at the triple A gasoline. 170 00:08:05,120 --> 00:08:06,760 Speaker 1: It's like, look, all these lines are going down. They 171 00:08:06,760 --> 00:08:09,400 Speaker 1: should show up. Can you talk a little bit about 172 00:08:09,520 --> 00:08:12,960 Speaker 1: why these legs exists, What is the difference between some 173 00:08:13,040 --> 00:08:16,200 Speaker 1: of these measured prices and the government prices and what 174 00:08:16,240 --> 00:08:19,360 Speaker 1: do you have any theories or sort of explanations why 175 00:08:19,640 --> 00:08:23,840 Speaker 1: past lags got disrupted? And so that the gap between 176 00:08:24,000 --> 00:08:26,920 Speaker 1: private survey measures of prices versus what showed up in 177 00:08:27,000 --> 00:08:30,320 Speaker 1: government data did not have the same temporal relationship as 178 00:08:30,360 --> 00:08:34,520 Speaker 1: it used to prepand the temporal is a good word. Yes, 179 00:08:34,559 --> 00:08:37,040 Speaker 1: I would I would talk about this with using you 180 00:08:37,080 --> 00:08:39,200 Speaker 1: know it'll go back to use cars. Yeah. One is 181 00:08:39,600 --> 00:08:41,920 Speaker 1: you know that in terms of the pandemic when it 182 00:08:42,000 --> 00:08:45,880 Speaker 1: hit um, what you had was basically a complete disruption 183 00:08:46,040 --> 00:08:48,560 Speaker 1: in the use cars marketing. So it wasn't just that 184 00:08:48,600 --> 00:08:51,160 Speaker 1: people demanded use cars because I say they were moving 185 00:08:51,200 --> 00:08:54,120 Speaker 1: in suburbs or whatever. The biggest ship was You've had 186 00:08:54,280 --> 00:08:57,800 Speaker 1: a natural seller in the used cars market. Car companies 187 00:08:58,160 --> 00:09:00,920 Speaker 1: who became a net buyer used to vehicles and we 188 00:09:01,000 --> 00:09:04,040 Speaker 1: really haven't seen that before. And what they did was 189 00:09:04,080 --> 00:09:06,559 Speaker 1: they scooped up all the zero to three year models 190 00:09:06,640 --> 00:09:09,920 Speaker 1: that they could to sort of replenish their stock. Um, 191 00:09:09,960 --> 00:09:11,800 Speaker 1: you know, things came back a lot stronger obviously twenty 192 00:09:11,840 --> 00:09:14,640 Speaker 1: one that people thought. So take a company like Davis. 193 00:09:14,960 --> 00:09:17,319 Speaker 1: They had about four hundred fifty thousand vehicles in their 194 00:09:17,320 --> 00:09:20,199 Speaker 1: fleet in two thousand. That got down to about two 195 00:09:20,400 --> 00:09:24,000 Speaker 1: d ninety thousand by the summer one, right when demand 196 00:09:24,040 --> 00:09:27,160 Speaker 1: was booted, So they couldn't replenish them for manufacturers. They 197 00:09:27,240 --> 00:09:29,920 Speaker 1: ended up going to the use cars market. So what 198 00:09:29,960 --> 00:09:32,480 Speaker 1: you found was pricing increases in the zero three year bucket, 199 00:09:32,480 --> 00:09:35,400 Speaker 1: which is all build buy those price increases skyrocket and 200 00:09:35,400 --> 00:09:37,480 Speaker 1: if you're a dealer trying to buy a car, you 201 00:09:37,520 --> 00:09:39,600 Speaker 1: can't find these vehicles and you need to go out 202 00:09:39,640 --> 00:09:42,000 Speaker 1: by four or five six yelds. So all across that age, 203 00:09:42,040 --> 00:09:43,880 Speaker 1: current prices spiked and it wasn't you know. I think 204 00:09:43,880 --> 00:09:46,559 Speaker 1: the issue is just the magnitude was so large that 205 00:09:46,800 --> 00:09:50,240 Speaker 1: you could really wait to price them out a retail right, 206 00:09:50,320 --> 00:09:52,920 Speaker 1: So you're paying way way more than you were used 207 00:09:52,960 --> 00:09:55,840 Speaker 1: to pay, and you had to pass that on a quickly. Uh. 208 00:09:55,920 --> 00:09:58,679 Speaker 1: And so I think we saw those lads disrupted for 209 00:09:58,840 --> 00:10:02,240 Speaker 1: that particular decide. Now on the way down, wholesales is 210 00:10:02,240 --> 00:10:04,800 Speaker 1: getting a lot cheaper, you can still sell it for 211 00:10:04,840 --> 00:10:07,440 Speaker 1: a bit more on the retail side. So again, just 212 00:10:07,480 --> 00:10:09,600 Speaker 1: like athlete, you kind of pocket the margins as long 213 00:10:09,640 --> 00:10:11,960 Speaker 1: as you can on the way down. And I think 214 00:10:11,960 --> 00:10:14,480 Speaker 1: that's what you're seeing. The other item I would actually 215 00:10:14,520 --> 00:10:18,560 Speaker 1: mention where honestly I am, I'm pretty stumbdusted. What's going 216 00:10:18,600 --> 00:10:22,400 Speaker 1: on is really furniture prices. Um. You know, we have 217 00:10:22,520 --> 00:10:26,120 Speaker 1: seen you talk about, you know, trucking rates going down, um, 218 00:10:26,360 --> 00:10:30,120 Speaker 1: import prices of furniture going down. Inventories are jumped, while 219 00:10:30,160 --> 00:10:32,840 Speaker 1: the big box retailers are telling you, you know, Walmart, Haargey, 220 00:10:32,840 --> 00:10:35,560 Speaker 1: we've got too much of the stuff that we're discounting heavily, 221 00:10:35,920 --> 00:10:38,000 Speaker 1: and yet the CPI is going up about one percent 222 00:10:38,360 --> 00:10:41,640 Speaker 1: you know, every single month. Um. And there, you know, 223 00:10:41,679 --> 00:10:43,679 Speaker 1: typically you would start to see the stuff coming through 224 00:10:43,720 --> 00:10:47,320 Speaker 1: pretty quickly. I've honestly been winning since March or April 225 00:10:47,400 --> 00:10:50,480 Speaker 1: for furniture to really slide, and it just continues to 226 00:10:50,480 --> 00:10:54,160 Speaker 1: sort of defy, um, defy expectations. So there, I don't 227 00:10:54,200 --> 00:10:57,160 Speaker 1: have as good as an answer in terms of what's happening, 228 00:10:57,200 --> 00:11:00,040 Speaker 1: but we know all the signs are planning to the 229 00:11:00,040 --> 00:11:03,040 Speaker 1: fact that they should be dropping, and the industry will 230 00:11:03,040 --> 00:11:05,600 Speaker 1: tell you that. I mean, you read any furniture industry 231 00:11:05,640 --> 00:11:08,280 Speaker 1: trade publication like I started doing when I was wrong 232 00:11:08,320 --> 00:11:11,120 Speaker 1: on furniture for a while, Um, you know, furniture to 233 00:11:11,160 --> 00:11:13,640 Speaker 1: a magazine will tell you, hey, they're preparing for recession. 234 00:11:14,040 --> 00:11:17,520 Speaker 1: They've got too much stuff, they're discounting, orders are declining, 235 00:11:18,080 --> 00:11:19,959 Speaker 1: and yet the CPI is that showing it. But I 236 00:11:20,000 --> 00:11:22,280 Speaker 1: will say one other thing to think about is some 237 00:11:22,320 --> 00:11:25,559 Speaker 1: of these samples in the CPI are not that large furniture. 238 00:11:25,600 --> 00:11:28,160 Speaker 1: If you're talking about bedroom furniture, they may only have 239 00:11:28,280 --> 00:11:32,040 Speaker 1: a couple of hundred quotes in the entire sample versus 240 00:11:32,440 --> 00:11:35,920 Speaker 1: you know, thousands for something like rent um or you 241 00:11:35,960 --> 00:11:39,319 Speaker 1: know thousand for airfare. So the smaller sample, the larger, 242 00:11:39,880 --> 00:11:42,400 Speaker 1: you know, the chance that you'll have some some errors, 243 00:11:42,440 --> 00:11:45,360 Speaker 1: you might miss some of the price changes, you know, 244 00:11:45,400 --> 00:11:48,080 Speaker 1: particular much so that can also impact the lads that 245 00:11:48,120 --> 00:11:51,319 Speaker 1: occur in the CPI. So, I mean it is true 246 00:11:51,400 --> 00:11:55,600 Speaker 1: on the whole, the goods inflation has been going down. 247 00:11:55,600 --> 00:11:58,880 Speaker 1: So I think it fell from like ten points seven 248 00:11:59,600 --> 00:12:03,400 Speaker 1: you know last year to seven point one last August. 249 00:12:04,120 --> 00:12:07,400 Speaker 1: And meanwhile, services, as we mentioned, is starting to pick 250 00:12:07,520 --> 00:12:09,880 Speaker 1: up and services correct me if I'm wrong, but I 251 00:12:09,880 --> 00:12:12,600 Speaker 1: think it's something like triple the weight in the core 252 00:12:12,640 --> 00:12:16,040 Speaker 1: indux something like that. Can you walk us through, like 253 00:12:16,200 --> 00:12:19,640 Speaker 1: a why do services get that much weighting and be 254 00:12:19,960 --> 00:12:22,800 Speaker 1: how significant is it for the core index that it's 255 00:12:22,840 --> 00:12:25,160 Speaker 1: now going up? Yes, so, I mean the bulk of 256 00:12:25,200 --> 00:12:28,640 Speaker 1: that weighting is is Shelter. It's it's rent and its 257 00:12:28,679 --> 00:12:31,439 Speaker 1: owner's equivalent rent um. You know, in the core CPI, 258 00:12:31,760 --> 00:12:33,920 Speaker 1: where do you present the entire core is just rent? 259 00:12:33,960 --> 00:12:37,920 Speaker 1: You know, we are combined and so within services, you know, 260 00:12:38,000 --> 00:12:40,840 Speaker 1: the bulk of the weight is coming from from Shelter. 261 00:12:41,000 --> 00:12:45,480 Speaker 1: So that's really what's driving UM that overweighting, if you will, 262 00:12:45,600 --> 00:12:48,640 Speaker 1: to services relative to two goods. The fact that it 263 00:12:48,840 --> 00:12:52,440 Speaker 1: is going up so dramatically, you know, that's obviously been 264 00:12:52,520 --> 00:12:55,640 Speaker 1: an issue for the core UM. I would really say 265 00:12:55,720 --> 00:13:00,640 Speaker 1: probably since since early spring when Shelter really started to accelerate. Now, 266 00:13:01,440 --> 00:13:03,640 Speaker 1: you know, one thing I want to mention UM is 267 00:13:03,679 --> 00:13:07,160 Speaker 1: that we I think the Shelter story, honestly is something 268 00:13:07,160 --> 00:13:11,000 Speaker 1: that most people knew was gonna happen coming into this year, right, 269 00:13:11,040 --> 00:13:13,720 Speaker 1: you mentioned some of these private market in the seas 270 00:13:13,760 --> 00:13:16,319 Speaker 1: like apartment lists and Zillo and so on. They were 271 00:13:16,360 --> 00:13:19,679 Speaker 1: showing these huge games and rents, you know, late last year, 272 00:13:20,120 --> 00:13:23,160 Speaker 1: last spraying, last summer, so we knew that this was 273 00:13:23,280 --> 00:13:25,360 Speaker 1: likely going to enter in the CPI this year. The 274 00:13:25,440 --> 00:13:28,160 Speaker 1: question was always about magnitude, so whether it was going 275 00:13:28,200 --> 00:13:30,760 Speaker 1: to be up six percent this year or seven percent, 276 00:13:30,800 --> 00:13:33,959 Speaker 1: which looks like we're headed for that some number. Um. 277 00:13:34,000 --> 00:13:36,840 Speaker 1: So to me, like, that's not really a surprise. On 278 00:13:36,880 --> 00:13:39,000 Speaker 1: the services side, I think most people who tracked this 279 00:13:39,040 --> 00:13:41,600 Speaker 1: stuff closely realized, hey, reds are gonna be up a 280 00:13:41,600 --> 00:13:44,680 Speaker 1: lot this year, probably someone in the six summers a range. 281 00:13:45,040 --> 00:13:47,959 Speaker 1: It's the other part of services and the non shelter 282 00:13:48,080 --> 00:13:51,280 Speaker 1: service stuff that I think is the more interesting part 283 00:13:51,600 --> 00:13:54,560 Speaker 1: of the story, and they're what you'll find is a 284 00:13:54,559 --> 00:13:57,400 Speaker 1: lot of people talking about how wages are driving those 285 00:13:57,440 --> 00:14:01,840 Speaker 1: services up. Um, you know how um all of these 286 00:14:01,840 --> 00:14:04,640 Speaker 1: other costs in the non shelter services, those are the 287 00:14:04,640 --> 00:14:07,760 Speaker 1: sticky elements of inflation. And until that stuff starts to 288 00:14:07,840 --> 00:14:09,880 Speaker 1: roll down, you know, it's gonna be really hard to 289 00:14:09,920 --> 00:14:13,680 Speaker 1: get correflation down. I would actually sort of counter that 290 00:14:13,720 --> 00:14:16,680 Speaker 1: a little bit by arguing that a lot of what 291 00:14:16,840 --> 00:14:19,440 Speaker 1: you've been seeing, and this has been true since really 292 00:14:19,560 --> 00:14:22,880 Speaker 1: last probably I would say fall, is we've had a 293 00:14:22,880 --> 00:14:26,280 Speaker 1: lot of oscillation in that non shelter service employment, and 294 00:14:26,360 --> 00:14:30,000 Speaker 1: that's mostly because of sort of the economy reopening and 295 00:14:30,040 --> 00:14:33,200 Speaker 1: closing and kind of fits its first. So summer of 296 00:14:33,200 --> 00:14:36,480 Speaker 1: twenty one, if you remember, airfare started to jump very significantly, 297 00:14:36,760 --> 00:14:39,120 Speaker 1: started traveling a bit again. So a lot of what 298 00:14:39,200 --> 00:14:41,480 Speaker 1: was driving services at that point was actually things like 299 00:14:41,560 --> 00:14:45,400 Speaker 1: affairs and hotels. It wasn't medical care services, it wasn't 300 00:14:45,440 --> 00:14:49,440 Speaker 1: recreation services, you know, it was really personal care services. 301 00:14:49,440 --> 00:14:51,960 Speaker 1: It was these sort of reopening categories, if you will. 302 00:14:52,520 --> 00:14:55,320 Speaker 1: Then you had you know, I think Delta was was 303 00:14:55,400 --> 00:14:58,440 Speaker 1: later in that year. Prices for those categories spell the 304 00:14:58,480 --> 00:15:02,920 Speaker 1: non shelter services inflation actually decelerate very sharply. So basically 305 00:15:02,960 --> 00:15:06,160 Speaker 1: what you've seen up until really pretty recently, it's just 306 00:15:06,360 --> 00:15:09,040 Speaker 1: this quarter to quarter oscillation that's been going on in 307 00:15:09,040 --> 00:15:13,080 Speaker 1: the non shelter um services in next really just reflecting 308 00:15:13,120 --> 00:15:16,560 Speaker 1: kind of the economy reopening and then slowing down. And 309 00:15:16,600 --> 00:15:18,560 Speaker 1: we got the same dynamic to spring, by the way, 310 00:15:18,600 --> 00:15:20,680 Speaker 1: when the airfare spite and now they've been down the 311 00:15:20,760 --> 00:15:23,120 Speaker 1: last few months, and so the non shelter stuff is 312 00:15:23,200 --> 00:15:41,800 Speaker 1: kind of moderating a little bit again. So let's talk 313 00:15:41,840 --> 00:15:44,520 Speaker 1: a little bit more on rent specifically for two reasons. 314 00:15:44,520 --> 00:15:47,360 Speaker 1: A because it is such a big part of uh, 315 00:15:47,440 --> 00:15:49,560 Speaker 1: you know, core cp I, but also it's one of 316 00:15:49,600 --> 00:15:52,320 Speaker 1: the most like people feel it and people complaining. Certainly 317 00:15:52,320 --> 00:15:54,960 Speaker 1: in New York everyone is aware of just like how 318 00:15:55,000 --> 00:15:59,880 Speaker 1: brutal the rent market is. But also elsewhere you mentioned there, 319 00:16:00,120 --> 00:16:03,240 Speaker 1: we sort of had reason to think that this number 320 00:16:03,320 --> 00:16:07,000 Speaker 1: was coming in part because the private surveys, We're flagging 321 00:16:07,040 --> 00:16:09,880 Speaker 1: this several of like maybe even a year ago, the 322 00:16:09,960 --> 00:16:13,320 Speaker 1: Zillois and all this. So for there reasons, one big 323 00:16:13,400 --> 00:16:16,480 Speaker 1: question which is like, is the data stale? And at 324 00:16:16,480 --> 00:16:18,680 Speaker 1: a time when people are worried about, oh are we 325 00:16:18,720 --> 00:16:20,840 Speaker 1: going to create is the Fed going to create a recession? 326 00:16:21,240 --> 00:16:24,080 Speaker 1: Is it being too aggressive? Uh? In light of you know, 327 00:16:24,160 --> 00:16:27,800 Speaker 1: is it whatever? Is it operating on old data that's 328 00:16:27,840 --> 00:16:31,560 Speaker 1: not as timely as what the private sector surveys are showing. 329 00:16:31,840 --> 00:16:35,440 Speaker 1: Is the public data stale? So I wouldn't necessarily say 330 00:16:35,560 --> 00:16:37,960 Speaker 1: it's scale. I would just say that it measures something 331 00:16:38,080 --> 00:16:41,160 Speaker 1: different than what these private sector indussees are measured. So 332 00:16:41,200 --> 00:16:44,760 Speaker 1: most of these private sector industries are measuring new leases. 333 00:16:45,160 --> 00:16:47,160 Speaker 1: So when you think about moving into a new apartment 334 00:16:47,200 --> 00:16:50,160 Speaker 1: beside a brand new lease, that's what they are capturing 335 00:16:50,200 --> 00:16:52,120 Speaker 1: and capturing that change in the right for that unit 336 00:16:52,200 --> 00:16:55,840 Speaker 1: with a new tenant versus whatever it ready for for 337 00:16:55,840 --> 00:16:58,680 Speaker 1: for the last ten And that's true of all most 338 00:16:58,680 --> 00:17:01,120 Speaker 1: of these apartment list of lists on and so it's 339 00:17:01,160 --> 00:17:05,040 Speaker 1: really just one segment of um the market that those 340 00:17:05,119 --> 00:17:08,560 Speaker 1: private private measures are capturing. The CPI is capturing the 341 00:17:08,760 --> 00:17:11,600 Speaker 1: entire rental markets. So it's not just people who are 342 00:17:11,640 --> 00:17:14,560 Speaker 1: looking for new apartments were signing new leases. It's also 343 00:17:14,600 --> 00:17:18,880 Speaker 1: people who are renewing their lease, and it's also people 344 00:17:18,920 --> 00:17:21,840 Speaker 1: who are currently renting and still all on the same 345 00:17:21,880 --> 00:17:25,120 Speaker 1: lease they were, you know, five months ago. So they 346 00:17:25,119 --> 00:17:27,760 Speaker 1: want to capture the entire market versus just a slice 347 00:17:27,840 --> 00:17:29,879 Speaker 1: of the market. So in that sense, I don't think 348 00:17:29,920 --> 00:17:33,120 Speaker 1: it's stale. Now that said, you know, when you think 349 00:17:33,160 --> 00:17:35,600 Speaker 1: about is a FED operating on old day, we do. 350 00:17:35,720 --> 00:17:38,080 Speaker 1: We do know that it lacks right before this very reason, 351 00:17:38,680 --> 00:17:42,240 Speaker 1: it doesn't capture the BLS, doesn't capture turning points in 352 00:17:42,320 --> 00:17:46,800 Speaker 1: the market as as well as these private sector measures. Right, 353 00:17:46,920 --> 00:17:49,880 Speaker 1: if if something is changing in the marketplace, those new 354 00:17:50,000 --> 00:17:52,440 Speaker 1: lease the way those new leases are changing is gonna 355 00:17:52,440 --> 00:17:55,480 Speaker 1: be a much better indicator what's happening then than the CPNI. 356 00:17:55,920 --> 00:17:59,040 Speaker 1: That's true. But it's not as if the Fed number 357 00:17:59,040 --> 00:18:02,320 Speaker 1: one doesn't watch their private sector measures, not that you know, 358 00:18:02,400 --> 00:18:04,600 Speaker 1: they don't understand the lags. I mean, if I understand 359 00:18:04,600 --> 00:18:07,879 Speaker 1: the lags that rent and other people do, I promise 360 00:18:07,920 --> 00:18:10,480 Speaker 1: you the folks that the FED do as well. Uh So, 361 00:18:11,400 --> 00:18:13,840 Speaker 1: I don't think that they are you know, sitting here 362 00:18:13,880 --> 00:18:16,760 Speaker 1: working on on the sort of lagging indicators if you will, 363 00:18:17,560 --> 00:18:21,040 Speaker 1: because they are. They're capturing in a huge amount of 364 00:18:21,119 --> 00:18:24,400 Speaker 1: data to look at what's happening in India shelter um 365 00:18:24,400 --> 00:18:27,560 Speaker 1: and they also kind of see where shelter is likely head. Right, 366 00:18:27,640 --> 00:18:30,080 Speaker 1: These private sector measures have started to roll over the 367 00:18:30,160 --> 00:18:32,040 Speaker 1: last you know, depending which one you want to look at, 368 00:18:33,000 --> 00:18:36,200 Speaker 1: four to seven months, they've been slowing down quite a bit. 369 00:18:36,680 --> 00:18:40,919 Speaker 1: So another thing related to housing and the cost of shelter, 370 00:18:41,000 --> 00:18:43,320 Speaker 1: which again it seems important because of the way and 371 00:18:43,359 --> 00:18:45,639 Speaker 1: just how much, not how important it is for the public. 372 00:18:46,119 --> 00:18:50,320 Speaker 1: We have seen a clear slow down in anything related 373 00:18:50,320 --> 00:18:52,840 Speaker 1: to home buying and home purchasing, and of course that 374 00:18:52,960 --> 00:18:56,960 Speaker 1: isn't I don't believe is that captured directly historically speaking? 375 00:18:57,200 --> 00:19:01,200 Speaker 1: Is there a relationship or a stable relationship between activity 376 00:19:01,200 --> 00:19:03,600 Speaker 1: and the home purchase market. The price of a house, 377 00:19:03,800 --> 00:19:06,280 Speaker 1: the price of a monthly mortgage, which is shot up 378 00:19:06,320 --> 00:19:08,359 Speaker 1: if you're just if you're buying a house today verse 379 00:19:08,359 --> 00:19:11,800 Speaker 1: a year ago, and then what feeds through into rent prices? 380 00:19:11,880 --> 00:19:13,040 Speaker 1: Can I just say that was going to be my 381 00:19:13,080 --> 00:19:15,919 Speaker 1: next question. We've been working together so long, we always 382 00:19:15,920 --> 00:19:17,600 Speaker 1: do that, We keep asking the same questions, But can 383 00:19:17,640 --> 00:19:19,919 Speaker 1: I tag onto that? So one thing I've heard is 384 00:19:20,320 --> 00:19:23,560 Speaker 1: there are some people who say that, like interest rates 385 00:19:23,600 --> 00:19:27,760 Speaker 1: going up could end up increasing the pressures on rent 386 00:19:27,920 --> 00:19:31,320 Speaker 1: because more people decide they're not going to buy houses right, 387 00:19:31,320 --> 00:19:33,560 Speaker 1: They're going to stay where they are, keep renting an 388 00:19:33,560 --> 00:19:36,840 Speaker 1: apartment and things like that. Yeah, so on that latter point, yes, 389 00:19:36,880 --> 00:19:39,840 Speaker 1: that's that's very possible. Um, you know, if it's getting 390 00:19:39,840 --> 00:19:42,080 Speaker 1: too expensive to get a mortgage, or you can't find 391 00:19:42,080 --> 00:19:44,600 Speaker 1: a house to buy, you renew your lease, or you 392 00:19:44,600 --> 00:19:48,120 Speaker 1: you know, are moving into the apartment, that certainly can 393 00:19:48,280 --> 00:19:51,919 Speaker 1: actually push rents up in the short term until supply 394 00:19:52,080 --> 00:19:54,439 Speaker 1: does eventually catch up. But yeah, that's that's very possible. 395 00:19:54,520 --> 00:19:57,280 Speaker 1: We've seen that happen before. Uh, in terms of the 396 00:19:57,320 --> 00:19:59,600 Speaker 1: idea of you know, the housing market and and her 397 00:19:59,720 --> 00:20:02,160 Speaker 1: versus activity. It really is kind of what you're talking about, 398 00:20:02,200 --> 00:20:04,800 Speaker 1: which is the knock on effect on the rental market. 399 00:20:05,160 --> 00:20:07,280 Speaker 1: That's really the way it's going to feed through into 400 00:20:07,320 --> 00:20:10,919 Speaker 1: the rent index because you know, contrary to popular belief, like, 401 00:20:11,119 --> 00:20:14,360 Speaker 1: house prices don't play any role whatsoever in the CPI 402 00:20:14,520 --> 00:20:18,080 Speaker 1: at all, um, even though owners Equivalent Rent Index, you know, 403 00:20:18,119 --> 00:20:21,159 Speaker 1: it's not intended to measure house prices. It basically is 404 00:20:21,320 --> 00:20:26,120 Speaker 1: using the contract rent data that they capture and sort 405 00:20:26,160 --> 00:20:28,960 Speaker 1: of you know, rejiggering it a little bit to to 406 00:20:29,040 --> 00:20:31,320 Speaker 1: come up with with, oh, we are but no house 407 00:20:31,320 --> 00:20:36,160 Speaker 1: price goes into the index whatsoever. The mortgage inter stuff, 408 00:20:36,200 --> 00:20:38,040 Speaker 1: you know, it used to actually be in the CPI 409 00:20:38,200 --> 00:20:40,879 Speaker 1: prior to nineteen eighty three because they just it was 410 00:20:40,920 --> 00:20:43,920 Speaker 1: a very different methodology back then, UM. And so when 411 00:20:43,960 --> 00:20:47,160 Speaker 1: when rates were moving higher and the cost of servicing 412 00:20:47,160 --> 00:20:50,679 Speaker 1: your mortgage moved up, that price actually was reflected in 413 00:20:50,680 --> 00:20:53,520 Speaker 1: the CPI back in the day. Um. But in nineteen 414 00:20:53,520 --> 00:20:55,439 Speaker 1: eighty three, there was a lot of different problems with 415 00:20:55,520 --> 00:20:57,639 Speaker 1: it um and they ended up switching out to this 416 00:20:57,680 --> 00:21:00,159 Speaker 1: new method of rental equivalence in net eight three. So 417 00:21:00,200 --> 00:21:02,240 Speaker 1: now that doesn't really play play much of the role 418 00:21:02,280 --> 00:21:04,359 Speaker 1: again other than the knock on effect on the rental 419 00:21:04,400 --> 00:21:08,200 Speaker 1: market in most houses. Is that how Vulcar defeated inflation 420 00:21:08,720 --> 00:21:12,040 Speaker 1: removing mortgage trains from It's like, we want to raise 421 00:21:12,119 --> 00:21:14,840 Speaker 1: rates to fight inflation, but our current measure of inflation 422 00:21:14,840 --> 00:21:17,760 Speaker 1: includes mortgages. Got to change the rules because otherwise our 423 00:21:17,920 --> 00:21:21,920 Speaker 1: rate you can regime won't help us at all. So actually, 424 00:21:22,119 --> 00:21:26,959 Speaker 1: in that instance, because of the rate increases, mortgage interest 425 00:21:27,000 --> 00:21:31,720 Speaker 1: costs in the CPI skyworketed and actually the inflation higher. 426 00:21:31,960 --> 00:21:33,919 Speaker 1: So even though he was boost in rates at the 427 00:21:33,920 --> 00:21:36,760 Speaker 1: same time you would think, okay, high rais you should 428 00:21:36,880 --> 00:21:40,040 Speaker 1: or inflation. In fact, inflation was moving higher partly because 429 00:21:40,040 --> 00:21:43,440 Speaker 1: mortgage interest costs were so much higher, and there was 430 00:21:43,440 --> 00:21:45,120 Speaker 1: a lot of problems with the idea of mortgage interest costs. 431 00:21:45,080 --> 00:21:48,040 Speaker 1: I mean, they knew about mortgage interns costs, and the 432 00:21:48,040 --> 00:21:51,439 Speaker 1: problems with sort of putting it into a cost of 433 00:21:51,520 --> 00:21:53,280 Speaker 1: living index. A lot of what you you know, a 434 00:21:53,280 --> 00:21:55,280 Speaker 1: lot of issues that people have with the CPI, whether 435 00:21:55,280 --> 00:21:58,760 Speaker 1: it's rents or other indexes is really about the constant 436 00:21:59,160 --> 00:22:01,720 Speaker 1: of how you design it, how you think about what 437 00:22:01,760 --> 00:22:05,159 Speaker 1: you should be capturing, and that fundamentally gets back to 438 00:22:05,200 --> 00:22:07,320 Speaker 1: the idea of you know, what is the purpose of 439 00:22:07,359 --> 00:22:09,679 Speaker 1: the CPI, and it's intended to be a cost of 440 00:22:09,800 --> 00:22:14,679 Speaker 1: living index UM And you know, they knew back I 441 00:22:14,680 --> 00:22:16,680 Speaker 1: think it was in seventies they had papers out the 442 00:22:16,720 --> 00:22:19,240 Speaker 1: b LS saying, look, we need to get away from this, 443 00:22:19,440 --> 00:22:22,040 Speaker 1: you know, mortgage interest costs because it doesn't really fit 444 00:22:22,119 --> 00:22:24,960 Speaker 1: the way that we're supposed to construct a CPO. You know, 445 00:22:25,000 --> 00:22:26,680 Speaker 1: you could do a whole separate episode on that, but 446 00:22:26,960 --> 00:22:30,439 Speaker 1: I think the short version is in three in eight 447 00:22:30,560 --> 00:22:33,120 Speaker 1: three they decided to say, hey, we've been talking about 448 00:22:33,160 --> 00:22:35,800 Speaker 1: this rental equivalence method for many years now, and we 449 00:22:35,840 --> 00:22:37,640 Speaker 1: think it's the right way to do it. By the way, 450 00:22:37,640 --> 00:22:40,359 Speaker 1: I will just say, very recently, UM National Caademy of 451 00:22:40,400 --> 00:22:44,000 Speaker 1: Sciences basically put out a report that said, you know, 452 00:22:44,080 --> 00:22:47,199 Speaker 1: here are our recommendations for improving the CPI in the 453 00:22:47,200 --> 00:22:50,240 Speaker 1: coming years. And they talked about looking at, you know, 454 00:22:50,280 --> 00:22:53,560 Speaker 1: these private measures of rent as potentially trying to incorporate 455 00:22:53,600 --> 00:22:56,080 Speaker 1: them into the CPI. But they said up until then 456 00:22:56,160 --> 00:22:58,120 Speaker 1: the best measure that we have is really the rental 457 00:22:58,160 --> 00:23:02,160 Speaker 1: equivalent method that we use today. Um, let me ask 458 00:23:02,160 --> 00:23:06,000 Speaker 1: a slightly less provocative question, um, other than how we 459 00:23:06,080 --> 00:23:10,520 Speaker 1: measure or don't measure mortgage interest in CBI. So historically, 460 00:23:10,840 --> 00:23:13,119 Speaker 1: one of the reasons we focus on rents is because 461 00:23:13,800 --> 00:23:16,520 Speaker 1: people feel them. Um, they're a big component of the 462 00:23:16,600 --> 00:23:19,920 Speaker 1: of the core index. But also because rents and wages 463 00:23:20,240 --> 00:23:23,720 Speaker 1: tend to be tightly linked. And I think there's concern 464 00:23:23,840 --> 00:23:27,480 Speaker 1: that as rent inflation accelerates, are we going to see 465 00:23:27,520 --> 00:23:32,040 Speaker 1: that knock on effect into wages. What are you seeing there? Yeah, 466 00:23:32,480 --> 00:23:35,320 Speaker 1: as you said, it is a pretty tight fit. I mean, basically, 467 00:23:35,320 --> 00:23:38,800 Speaker 1: I would saying labor income and and rent growth are 468 00:23:38,920 --> 00:23:43,400 Speaker 1: are pretty tightly correlated. Um. You know again, I think 469 00:23:43,600 --> 00:23:46,359 Speaker 1: as rents have gone up, they correlated well with this 470 00:23:46,560 --> 00:23:50,040 Speaker 1: improvement in wage growth. One of the interesting sort of 471 00:23:50,080 --> 00:23:53,520 Speaker 1: tickets is that a lot of even though rents are rising, 472 00:23:53,600 --> 00:23:56,520 Speaker 1: a lot of people who are reapinger pleases are actually 473 00:23:56,600 --> 00:23:59,240 Speaker 1: or side new leases in you know, sort of more 474 00:23:59,640 --> 00:24:02,760 Speaker 1: profess she manage department buildings. So more of your large 475 00:24:02,840 --> 00:24:07,640 Speaker 1: multifamily in the buildings are actually showing that their incomes 476 00:24:07,640 --> 00:24:10,879 Speaker 1: have increased pretty significantly over the last two years. So 477 00:24:10,960 --> 00:24:12,720 Speaker 1: even though we talk about you know, the idea of 478 00:24:12,760 --> 00:24:14,639 Speaker 1: a lot of people getting priced out because rents are 479 00:24:14,680 --> 00:24:17,320 Speaker 1: rising so sharply, people who are citing new leases and 480 00:24:17,359 --> 00:24:20,080 Speaker 1: having to provide the paperwork from their bank statements or 481 00:24:20,320 --> 00:24:24,480 Speaker 1: or you know, their their employment information are showing that 482 00:24:24,600 --> 00:24:27,960 Speaker 1: incomes have actually also increased pretty significantly. And so I think, 483 00:24:28,040 --> 00:24:30,679 Speaker 1: you know, as you start to see wage growth decelerate 484 00:24:30,720 --> 00:24:32,760 Speaker 1: a little bit, which is already starting to happen at 485 00:24:32,760 --> 00:24:36,720 Speaker 1: the margins um. You know, people who manage these apartments 486 00:24:36,720 --> 00:24:38,879 Speaker 1: sort of they get this kind of real time flow 487 00:24:39,000 --> 00:24:42,920 Speaker 1: of what labor income looks like. And I think that's 488 00:24:42,960 --> 00:24:46,280 Speaker 1: partly also why you odesty rents start to decelerate is 489 00:24:46,320 --> 00:24:49,000 Speaker 1: because they're not reasoning rent six percent when they see 490 00:24:49,040 --> 00:24:51,800 Speaker 1: labor income only. Yeah, let's say it's where did you 491 00:24:51,840 --> 00:24:54,199 Speaker 1: get where's that data from? That the people that the 492 00:24:54,280 --> 00:24:58,119 Speaker 1: cohort that is turning new leases is actually seeing wage 493 00:24:58,160 --> 00:25:00,840 Speaker 1: games that are keeping up with rent. Yeah, and that 494 00:25:00,840 --> 00:25:03,679 Speaker 1: comes from real page um. And that's another you know, 495 00:25:03,760 --> 00:25:08,200 Speaker 1: large sort of private market provider of everything from rent 496 00:25:08,280 --> 00:25:12,240 Speaker 1: data to all sorts of information on multiply buildings. Um, 497 00:25:12,320 --> 00:25:14,760 Speaker 1: and so they've been tracking this and sort of publishing 498 00:25:14,880 --> 00:25:16,880 Speaker 1: you know, stories on this for the last I think 499 00:25:16,880 --> 00:25:19,640 Speaker 1: about eighteen months or so, just this idea that even 500 00:25:19,640 --> 00:25:22,919 Speaker 1: though rents are are moving higher, people are able to 501 00:25:23,000 --> 00:25:27,360 Speaker 1: afford those rights because their incomes are arising alongside those 502 00:25:27,440 --> 00:25:30,520 Speaker 1: those rankings as well. So one other question on rent 503 00:25:30,560 --> 00:25:32,560 Speaker 1: before we go off it, and again it sort of 504 00:25:32,600 --> 00:25:37,840 Speaker 1: connects to uh broader housing questions. Uh. A lot of 505 00:25:37,840 --> 00:25:39,560 Speaker 1: people I think, in the last couple of years when 506 00:25:39,640 --> 00:25:42,960 Speaker 1: rates were low, bought houses as investment properties and maybe 507 00:25:42,960 --> 00:25:44,639 Speaker 1: don't want to sell right now in part because there 508 00:25:44,640 --> 00:25:48,320 Speaker 1: aren't a lot of buyers who are excited about the 509 00:25:48,320 --> 00:25:51,080 Speaker 1: sticker shock of what a monthly mortgage now cost them. 510 00:25:51,359 --> 00:25:55,239 Speaker 1: Could this bring more rental supply to market in your views, like, well, 511 00:25:55,280 --> 00:25:56,879 Speaker 1: I can't sell it, so I rented, and could that 512 00:25:56,960 --> 00:26:00,119 Speaker 1: have a dampening effect on rents? Yeah, very possibly. I mean, 513 00:26:00,640 --> 00:26:04,560 Speaker 1: most indusseries don't trap single family rentals. The only one 514 00:26:04,560 --> 00:26:07,480 Speaker 1: that I'm aware of that does is it's either zill 515 00:26:07,520 --> 00:26:09,600 Speaker 1: or poor logic. It's one of those who has a 516 00:26:09,680 --> 00:26:13,040 Speaker 1: single family right index where they do track what rents 517 00:26:13,160 --> 00:26:16,119 Speaker 1: are specifically for that sort of you know for that 518 00:26:16,200 --> 00:26:19,600 Speaker 1: type of rental um. And yeah, obviously if you can't 519 00:26:19,640 --> 00:26:21,719 Speaker 1: sell it and you want it as best investment property, 520 00:26:21,760 --> 00:26:24,159 Speaker 1: it makes quite a lot of sense given that, you know, 521 00:26:24,240 --> 00:26:27,760 Speaker 1: demand is still pretty robust for for rentals. Vacancy rates 522 00:26:27,800 --> 00:26:31,919 Speaker 1: have only barely started to edge higher from the lows 523 00:26:31,960 --> 00:26:35,040 Speaker 1: that we saw, you know, even six months ago, so 524 00:26:35,080 --> 00:26:36,600 Speaker 1: there's still quite a lot of demand out there, So 525 00:26:36,680 --> 00:26:38,920 Speaker 1: it makes sense to do that at this stage. And yeah, 526 00:26:38,960 --> 00:26:41,760 Speaker 1: hopefully that can help bring at least that one segment 527 00:26:41,960 --> 00:26:44,760 Speaker 1: of of rent of the rental market down. And by 528 00:26:44,800 --> 00:26:47,119 Speaker 1: the way, that is also captured in the CPI, right, 529 00:26:47,200 --> 00:26:49,159 Speaker 1: the CPI isn't when we're talking about rents, it's not 530 00:26:49,240 --> 00:26:54,160 Speaker 1: just apartments. They also to capture um single family rentals 531 00:26:54,240 --> 00:27:13,120 Speaker 1: in that entire sample as well. So we've been talking 532 00:27:13,160 --> 00:27:16,480 Speaker 1: a lot about rents um which have been pushing services 533 00:27:16,680 --> 00:27:20,119 Speaker 1: up higher, but are at the point you've been making, 534 00:27:20,160 --> 00:27:23,159 Speaker 1: are expected to start to decrease sometime soon, or at 535 00:27:23,200 --> 00:27:26,120 Speaker 1: least the rate of acceleration will start slowing down. Talk 536 00:27:26,160 --> 00:27:30,199 Speaker 1: to us about another big change that you see potentially 537 00:27:30,240 --> 00:27:33,280 Speaker 1: on the horizon that has to do with healthcare. Yeah, 538 00:27:33,280 --> 00:27:35,680 Speaker 1: so this is another one that I think is it's 539 00:27:35,760 --> 00:27:38,760 Speaker 1: coming very soon. It's gonna it's gonna help everyone looking 540 00:27:38,760 --> 00:27:46,680 Speaker 1: for that transitory in place story. Yes, you know kind yeah, so, um, 541 00:27:46,720 --> 00:27:48,320 Speaker 1: you know, right, as I mentioned the biggest part of 542 00:27:48,320 --> 00:27:53,159 Speaker 1: the course, the second biggest component is medical care UM. 543 00:27:53,160 --> 00:27:56,639 Speaker 1: That's worth just about of the court. And for the 544 00:27:56,760 --> 00:28:00,320 Speaker 1: last year, medical care has been rising in about, you know, 545 00:28:00,440 --> 00:28:04,280 Speaker 1: roughly zero point five percent in each month, which means 546 00:28:04,280 --> 00:28:07,480 Speaker 1: it's been adding about five basis points to the core 547 00:28:07,840 --> 00:28:10,600 Speaker 1: change every single month. That's been very set. It's kind 548 00:28:10,600 --> 00:28:14,040 Speaker 1: of like clockwork pretty much all all of last year. UM. 549 00:28:14,080 --> 00:28:16,479 Speaker 1: Starting in termre that index is going to turn negative 550 00:28:17,320 --> 00:28:20,600 Speaker 1: and it's gonna turn negative in most months over the 551 00:28:20,600 --> 00:28:24,679 Speaker 1: course of the next year. And so what was a 552 00:28:24,760 --> 00:28:28,880 Speaker 1: pretty constant um source of a boost to the core 553 00:28:28,960 --> 00:28:32,199 Speaker 1: every single month is actually going to turn into a 554 00:28:32,320 --> 00:28:36,720 Speaker 1: relatively decent drag on the core. And you know it's 555 00:28:36,760 --> 00:28:40,160 Speaker 1: not because medical care is getting cheaper or so on. Uh, 556 00:28:40,200 --> 00:28:41,920 Speaker 1: this is actually just one of these works in the 557 00:28:41,960 --> 00:28:45,360 Speaker 1: methodology that you kind of have to be aware of, UM, 558 00:28:45,400 --> 00:28:49,080 Speaker 1: and it comes very specifically from the health insurance index 559 00:28:49,320 --> 00:28:52,960 Speaker 1: within the broader medical care gage. Well, what's the me 560 00:28:53,200 --> 00:28:55,120 Speaker 1: So what is that change that's coming. Why is it's 561 00:28:55,280 --> 00:28:58,120 Speaker 1: what is going to switch from pushing up to being 562 00:28:58,120 --> 00:29:01,040 Speaker 1: a drag. Yeah. So so the story is basically that 563 00:29:01,280 --> 00:29:04,280 Speaker 1: first of all, health insurance is updated once a year, 564 00:29:04,400 --> 00:29:07,560 Speaker 1: typically in the October used to be September. Last year 565 00:29:07,600 --> 00:29:09,560 Speaker 1: was October. This year will be in the October report 566 00:29:09,600 --> 00:29:13,240 Speaker 1: again um. But this data lacks by almost about a 567 00:29:13,400 --> 00:29:16,120 Speaker 1: year UM. So the BLS takes the state of and 568 00:29:16,160 --> 00:29:18,760 Speaker 1: this is from an official source, the National Association of 569 00:29:18,800 --> 00:29:21,200 Speaker 1: Insurance Commissioners, So this is sort of you know, they 570 00:29:21,600 --> 00:29:24,800 Speaker 1: put out a big report on how much in premiums 571 00:29:24,840 --> 00:29:26,640 Speaker 1: has been collected and how much is being paid out 572 00:29:26,680 --> 00:29:29,440 Speaker 1: and how much is retained by insure. So this is 573 00:29:29,480 --> 00:29:32,600 Speaker 1: kind of the holy grail of this data set. Unfortunately, 574 00:29:32,600 --> 00:29:34,640 Speaker 1: it doesn't come out until that ten months apt into 575 00:29:34,680 --> 00:29:37,560 Speaker 1: the year, and so what we're really capturing this October 576 00:29:37,720 --> 00:29:39,840 Speaker 1: is going to be activity that happened in two thousand 577 00:29:39,920 --> 00:29:42,560 Speaker 1: twenty one. And so what's can happen here is that 578 00:29:42,600 --> 00:29:46,640 Speaker 1: if you think about and during the pandemic, people you know, 579 00:29:46,680 --> 00:29:49,760 Speaker 1: put off things like elective surgeries. They didn't go to 580 00:29:49,800 --> 00:29:51,840 Speaker 1: the doctor because people didn't want to be waiting, you know, 581 00:29:51,880 --> 00:29:55,000 Speaker 1: in waiting rooms with other people who might have COVID, right, 582 00:29:55,480 --> 00:29:59,560 Speaker 1: so there just wasn't a lot of utilization of healthcare services. 583 00:29:59,720 --> 00:30:03,520 Speaker 1: To US twenty premium income continue to increase, but the 584 00:30:03,560 --> 00:30:08,120 Speaker 1: benefits paid out actually declined. The way the CPI captures 585 00:30:08,240 --> 00:30:12,160 Speaker 1: health insurance is by looking at the change in these 586 00:30:12,240 --> 00:30:15,120 Speaker 1: retained earnings for insurance from one year to the next, 587 00:30:15,680 --> 00:30:17,600 Speaker 1: and you know very quickly. The reason they do this 588 00:30:17,760 --> 00:30:22,080 Speaker 1: is because it's really hard to price health insurance from 589 00:30:22,080 --> 00:30:25,240 Speaker 1: one month to the next because policies are changing all 590 00:30:25,240 --> 00:30:28,200 Speaker 1: the time. Right The what what a policy will cover 591 00:30:28,880 --> 00:30:32,000 Speaker 1: will be could be changing quarterly, monthly, you know, each year, 592 00:30:32,720 --> 00:30:34,960 Speaker 1: the risk factors that go into the policy can change. 593 00:30:35,320 --> 00:30:37,560 Speaker 1: So when the billness is pricing any good or service, 594 00:30:37,640 --> 00:30:39,720 Speaker 1: they want apples to apples from one of months to 595 00:30:39,760 --> 00:30:42,720 Speaker 1: the next, and if something changes, they want a quality adjusted. 596 00:30:43,400 --> 00:30:45,760 Speaker 1: But in healthcare and health insurance, they found that's just 597 00:30:45,840 --> 00:30:49,080 Speaker 1: way way too hard to do. So the roundabout way 598 00:30:49,120 --> 00:30:52,120 Speaker 1: of this indirect way of capturing the price to you, 599 00:30:52,360 --> 00:30:55,800 Speaker 1: the consumer of health insurance is basically, what does it 600 00:30:55,880 --> 00:30:59,800 Speaker 1: cost the business to offer you health insurance if they're 601 00:31:00,000 --> 00:31:03,680 Speaker 1: also administering health services or health insurance is rising, you'll 602 00:31:03,720 --> 00:31:07,280 Speaker 1: probably see that in your premiums, and so the way 603 00:31:07,320 --> 00:31:09,680 Speaker 1: they captured this by looking at these retained earnings and 604 00:31:09,720 --> 00:31:11,960 Speaker 1: how they're changing from one year to the next. So 605 00:31:12,080 --> 00:31:17,200 Speaker 1: during the pandemic, premiums kept rising. However, benefits paid out 606 00:31:17,240 --> 00:31:20,640 Speaker 1: to people went down quite substantially because of COVID and 607 00:31:20,880 --> 00:31:23,400 Speaker 1: the lack of utilization of healthcare. So what you saw 608 00:31:23,480 --> 00:31:27,640 Speaker 1: was a huge spike in retained earnings. And what that 609 00:31:27,680 --> 00:31:31,040 Speaker 1: meant for the cp I was that in October of 610 00:31:31,120 --> 00:31:36,520 Speaker 1: two thousand twenty one, which reflective is health insurance jumped 611 00:31:36,520 --> 00:31:40,480 Speaker 1: by two in the month of two which means that basically, 612 00:31:40,520 --> 00:31:43,640 Speaker 1: since you only updated once a year, it's effectively going 613 00:31:43,720 --> 00:31:47,440 Speaker 1: to print right around two percent every single month like clockwork. 614 00:31:47,880 --> 00:31:52,520 Speaker 1: Until the next Sunday fast forward, people started, you know, 615 00:31:52,840 --> 00:31:55,800 Speaker 1: going back and taking care of these elective surgeries and 616 00:31:56,000 --> 00:32:00,040 Speaker 1: utilizing healthcare much much more than they did premiums. It 617 00:32:00,320 --> 00:32:03,880 Speaker 1: really changed to dramatically. So now you have a SIS 618 00:32:03,960 --> 00:32:06,680 Speaker 1: match again where way more utilization of health care than 619 00:32:06,720 --> 00:32:13,080 Speaker 1: you had, and so then those retained earnings dropped on 620 00:32:13,120 --> 00:32:16,280 Speaker 1: a year a year basis. So what's going to happen 621 00:32:16,320 --> 00:32:19,040 Speaker 1: now when you update it is that you're going to 622 00:32:19,160 --> 00:32:21,760 Speaker 1: have a very large drag. So health insurance, which has 623 00:32:21,800 --> 00:32:25,600 Speaker 1: been two months pretty much for the last year, is 624 00:32:25,720 --> 00:32:28,600 Speaker 1: very likely to print in an October report around minus 625 00:32:28,640 --> 00:32:31,480 Speaker 1: four percent. You know, on the surface, you say, well, 626 00:32:31,520 --> 00:32:33,680 Speaker 1: plus two to minus four that doesn't really sound like 627 00:32:33,720 --> 00:32:36,360 Speaker 1: a lot, but if you kind of put it into context, 628 00:32:36,360 --> 00:32:39,000 Speaker 1: it actually is is kind of dramatic because number one 629 00:32:39,400 --> 00:32:42,560 Speaker 1: in the month of October itself, that alone is worth 630 00:32:42,600 --> 00:32:45,680 Speaker 1: almost a seven basis points swing on just a course tPON. 631 00:32:46,160 --> 00:32:48,280 Speaker 1: So if you're forecasting let's say the core and you 632 00:32:48,280 --> 00:32:50,920 Speaker 1: get a point forward in October, you're probably looking at 633 00:32:50,960 --> 00:32:53,760 Speaker 1: something that's more like a point through instead, just because 634 00:32:53,760 --> 00:32:56,320 Speaker 1: of this movement in health insurance. And you know, that's 635 00:32:56,400 --> 00:32:58,320 Speaker 1: kind of the difference between a five percent in realize 636 00:32:58,400 --> 00:33:00,400 Speaker 1: rate and you know something that's more like a three 637 00:33:00,440 --> 00:33:02,280 Speaker 1: and a half percent in US. So that's a pretty 638 00:33:02,400 --> 00:33:05,280 Speaker 1: big gap. The other issues here. On a year a 639 00:33:05,360 --> 00:33:08,800 Speaker 1: year basis, health insurance currently is about twenty five percent 640 00:33:08,880 --> 00:33:11,480 Speaker 1: year year because of the steady you know, two percent 641 00:33:11,520 --> 00:33:14,440 Speaker 1: hours every month. When the next report comes out September, 642 00:33:14,440 --> 00:33:16,760 Speaker 1: which is sort of the last herald before it, terms 643 00:33:16,760 --> 00:33:21,760 Speaker 1: of negative will probably hit at once this minus four 644 00:33:21,840 --> 00:33:24,240 Speaker 1: comes in in October and it stays here for the 645 00:33:24,280 --> 00:33:28,280 Speaker 1: bulk of the year. By September three, Health Insurance I 646 00:33:28,640 --> 00:33:32,400 Speaker 1: suspect we'll go from plus twenty eight to about minus four. 647 00:33:32,880 --> 00:33:38,720 Speaker 1: Ye're here. That swing is worth almost about any basis 648 00:33:38,760 --> 00:33:42,440 Speaker 1: points on the core CPI. So you have an index 649 00:33:42,520 --> 00:33:46,760 Speaker 1: that's worth just over one percent of the entire course 650 00:33:46,800 --> 00:33:52,080 Speaker 1: CPI that by itself will subtract almost a full percentage 651 00:33:52,080 --> 00:33:57,320 Speaker 1: point from cornflation. An extreme that's is so crazy to 652 00:33:57,360 --> 00:33:59,440 Speaker 1: be because the whole point of like measuring the stuff 653 00:33:59,440 --> 00:34:03,440 Speaker 1: and then mondetary policies like countercyclical and this huge component 654 00:34:03,760 --> 00:34:07,600 Speaker 1: as you just described, it has no there's no actual 655 00:34:07,720 --> 00:34:11,239 Speaker 1: like economically cyclical impulse part of it. Well, this was 656 00:34:11,280 --> 00:34:13,719 Speaker 1: actually going to be my next question, and oh, Mary, 657 00:34:13,800 --> 00:34:17,200 Speaker 1: that was absolutely fascinating. And the thing about qualitative adjustments 658 00:34:17,400 --> 00:34:20,799 Speaker 1: was something that I only like really discovered this year, 659 00:34:20,880 --> 00:34:22,960 Speaker 1: so I didn't know the BLS, you know, if they're 660 00:34:22,960 --> 00:34:25,759 Speaker 1: looking at the cost of a refrigerator, for instance, will 661 00:34:25,760 --> 00:34:29,120 Speaker 1: take into account technological advances on the cost of the 662 00:34:29,160 --> 00:34:31,720 Speaker 1: refrigerator if it now comes with I don't know, WiFi 663 00:34:31,800 --> 00:34:36,520 Speaker 1: connectivity or something, yeah, blockchain enabled fridge um and they 664 00:34:36,560 --> 00:34:39,640 Speaker 1: will factor that into the c p I. But I 665 00:34:39,640 --> 00:34:42,680 Speaker 1: mean this gets to one of the major criticisms of 666 00:34:42,719 --> 00:34:45,200 Speaker 1: the indices themselves. You can kind of see what they're 667 00:34:45,239 --> 00:34:49,720 Speaker 1: trying to do, so it's difficult to measure qualitative improvements 668 00:34:50,360 --> 00:34:54,640 Speaker 1: in things like healthcare insurance. But on the other hand, 669 00:34:54,880 --> 00:34:58,359 Speaker 1: it does lead people to look at these things and go, well, 670 00:34:58,400 --> 00:35:00,880 Speaker 1: what are we actually measuring here? And isn't it weird 671 00:35:00,960 --> 00:35:03,239 Speaker 1: that the cost of living, you know, as measured by 672 00:35:03,239 --> 00:35:07,719 Speaker 1: the CPI, which includes rent, healthcare, food, energy, whatever, can 673 00:35:07,840 --> 00:35:10,919 Speaker 1: change just because of like the way this one thing 674 00:35:11,520 --> 00:35:15,280 Speaker 1: is measured retained earnings versus the way we measure goods 675 00:35:15,280 --> 00:35:17,680 Speaker 1: and things like that. What do you say to that 676 00:35:17,760 --> 00:35:21,600 Speaker 1: criticisms It's fair to to make those sorts of criticisms. 677 00:35:21,640 --> 00:35:23,759 Speaker 1: I guess I would say couple. One thing is that 678 00:35:24,560 --> 00:35:27,600 Speaker 1: you know, this is never a static process in terms 679 00:35:27,719 --> 00:35:31,400 Speaker 1: of the methodology, so the BLS is always trying to 680 00:35:31,440 --> 00:35:35,760 Speaker 1: improve upon whatever is that they're doing. A good example 681 00:35:35,840 --> 00:35:39,080 Speaker 1: of this something like new vehicles. Um just in April 682 00:35:39,120 --> 00:35:41,080 Speaker 1: of this year, in fact, they introduced a brand new 683 00:35:41,120 --> 00:35:44,480 Speaker 1: methodology for capturing the price of new vehicles. So before 684 00:35:44,520 --> 00:35:47,160 Speaker 1: they used to go to dealers figure apples selling, you know, 685 00:35:47,200 --> 00:35:50,480 Speaker 1: try to capture those prices. Now they're using a massive 686 00:35:50,560 --> 00:35:54,680 Speaker 1: data set from Shady Power, which captures you know, essentially 687 00:35:54,760 --> 00:35:59,160 Speaker 1: real live transactions that are occurring. So they've updated that 688 00:35:59,440 --> 00:36:01,480 Speaker 1: quite in the forget me to really reflect kind of 689 00:36:01,480 --> 00:36:03,920 Speaker 1: the conditions on the ground for people who are providing 690 00:36:03,920 --> 00:36:08,640 Speaker 1: new cards. So there's always there's always this sort of, uh, 691 00:36:08,719 --> 00:36:12,239 Speaker 1: you know, goal to improve upon the methodology. So that's 692 00:36:12,280 --> 00:36:14,719 Speaker 1: that's number one. Number two is you know, you kind 693 00:36:14,719 --> 00:36:17,040 Speaker 1: of do the best you can with what you're given. 694 00:36:17,280 --> 00:36:19,759 Speaker 1: And by that I mean that a lot of these 695 00:36:19,800 --> 00:36:24,200 Speaker 1: things are subject to things like budget constraints. Um, you know, 696 00:36:24,360 --> 00:36:27,360 Speaker 1: when we talk about the rent for example, the BLS, 697 00:36:27,440 --> 00:36:29,839 Speaker 1: if you survey a unit, let's say in January, and 698 00:36:29,840 --> 00:36:32,000 Speaker 1: you say, hey, how much you're paying the rent? You 699 00:36:32,080 --> 00:36:33,680 Speaker 1: come back to that unit, you don't come back to 700 00:36:33,719 --> 00:36:35,440 Speaker 1: in February or March rate whill you come back to 701 00:36:35,480 --> 00:36:38,759 Speaker 1: it in July six months later. Part of the rationalist 702 00:36:38,840 --> 00:36:41,759 Speaker 1: because you know, rents don't change a lot in terms 703 00:36:41,760 --> 00:36:44,600 Speaker 1: of the contracts, so six months seem like an adequate 704 00:36:44,640 --> 00:36:47,239 Speaker 1: amount of time. But the two other reasons are one, 705 00:36:47,320 --> 00:36:50,480 Speaker 1: respondent burden, Right, if I'm knocking on your door every 706 00:36:50,520 --> 00:36:52,200 Speaker 1: single amount asking where the rent is, you might be 707 00:36:52,280 --> 00:36:55,120 Speaker 1: less willing to participate in the survey. But the other 708 00:36:55,200 --> 00:36:58,279 Speaker 1: is also there's a budget much terry constraint involved here 709 00:36:58,800 --> 00:37:00,839 Speaker 1: in terms of you know, sending people out into the 710 00:37:00,880 --> 00:37:04,000 Speaker 1: field to capture a lot of these data sets. Um, 711 00:37:04,040 --> 00:37:07,239 Speaker 1: so that all of these things sort of constrain what 712 00:37:07,960 --> 00:37:11,360 Speaker 1: uh you know, the BLS can ultimately produce in this 713 00:37:11,440 --> 00:37:13,879 Speaker 1: particular instance for health insurance. You know, I can sort 714 00:37:13,880 --> 00:37:15,520 Speaker 1: of understand a bit more of the criticism, but the 715 00:37:15,600 --> 00:37:19,239 Speaker 1: issue here is really the data is just black ten months. Um, 716 00:37:19,560 --> 00:37:21,520 Speaker 1: we can't do anything about that. I mean, the data 717 00:37:21,600 --> 00:37:25,440 Speaker 1: that they are getting is from the National Association of 718 00:37:25,440 --> 00:37:28,560 Speaker 1: Insurance Issues. And if you think about capturing all of 719 00:37:28,600 --> 00:37:32,080 Speaker 1: the premium inverture, all of the claims that are paying 720 00:37:32,120 --> 00:37:34,440 Speaker 1: by all of these health insurers, you know, it just 721 00:37:34,480 --> 00:37:36,319 Speaker 1: takes up for for the last year. It just takes 722 00:37:36,320 --> 00:37:38,600 Speaker 1: a while to put those numbers together. So this is 723 00:37:38,640 --> 00:37:40,920 Speaker 1: just something with the BLS just has to wait on 724 00:37:41,560 --> 00:37:44,520 Speaker 1: the data that they're capturing. Again, this that data set 725 00:37:44,560 --> 00:37:46,680 Speaker 1: is you know, effectively like the bible for for health 726 00:37:46,680 --> 00:37:50,360 Speaker 1: insurance data, right, and so this istance they can't do anything. 727 00:37:50,360 --> 00:37:53,920 Speaker 1: They just have to wait until that's produced. UM. So 728 00:37:54,000 --> 00:37:55,640 Speaker 1: I think you know, in some instances that I get 729 00:37:55,640 --> 00:37:57,920 Speaker 1: the criticism. I just think you've got to understand that 730 00:37:57,920 --> 00:38:02,080 Speaker 1: they were working within a number of different constraints, UM, 731 00:38:02,120 --> 00:38:04,839 Speaker 1: and you know sort of take that into account when 732 00:38:04,840 --> 00:38:10,560 Speaker 1: you're thinking about criticizing them for particular approaches, UM, in 733 00:38:10,680 --> 00:38:14,440 Speaker 1: terms of, uh, you know, how they constructed it. Can 734 00:38:14,480 --> 00:38:16,440 Speaker 1: we do a live event if you wondering where people 735 00:38:16,600 --> 00:38:19,319 Speaker 1: throw out a CPI category and then you like on 736 00:38:19,400 --> 00:38:21,440 Speaker 1: the fly explained No, I serious, people would love to 737 00:38:21,480 --> 00:38:24,399 Speaker 1: explain how it's constructed because we could this. We could 738 00:38:24,440 --> 00:38:27,640 Speaker 1: just talk forever on every category. I found this conversation. Seriously, 739 00:38:27,640 --> 00:38:30,319 Speaker 1: Can we can we do that someday? Yeah, there's you know, 740 00:38:30,360 --> 00:38:34,240 Speaker 1: there's uh two hundred forty three individual components and the CPI. 741 00:38:34,320 --> 00:38:36,600 Speaker 1: I love it. I think I've got most of them 742 00:38:36,600 --> 00:38:39,800 Speaker 1: down that we could probably do that. Other facts and oils, 743 00:38:39,800 --> 00:38:43,320 Speaker 1: including peanut butter. Yeah, I can. I didn't say. I 744 00:38:43,480 --> 00:38:47,200 Speaker 1: didn't say we could do the PPI. Okay, that's true. Wow, 745 00:38:47,239 --> 00:38:49,920 Speaker 1: you actually knew that was a PPI code versus the CPI. 746 00:38:50,080 --> 00:38:53,800 Speaker 1: That's verysive. We talked about one final thing. I just 747 00:38:53,840 --> 00:38:55,600 Speaker 1: wanted to be showing the self insurance stuff is that 748 00:38:55,920 --> 00:38:57,120 Speaker 1: you know. Part of the reason why I think it 749 00:38:57,200 --> 00:39:01,200 Speaker 1: is pretty important is because this to set uh, the 750 00:39:01,239 --> 00:39:03,680 Speaker 1: official report is coming out and thinking about a week. 751 00:39:03,760 --> 00:39:06,799 Speaker 1: I tend to use separate source, which is you know 752 00:39:06,840 --> 00:39:09,800 Speaker 1: carverage quite well. But basically, you know, my feeling is 753 00:39:09,840 --> 00:39:13,080 Speaker 1: that folks who are either treating in place shan or 754 00:39:13,120 --> 00:39:17,120 Speaker 1: who just generally following play shit are pretty unaware of this, 755 00:39:17,120 --> 00:39:19,960 Speaker 1: this change that's coming. So this is gonna be something 756 00:39:20,000 --> 00:39:22,239 Speaker 1: that you know, is at the margin going to help 757 00:39:22,320 --> 00:39:26,600 Speaker 1: the FED month over month for the next year, along 758 00:39:26,600 --> 00:39:28,080 Speaker 1: with I think the coming to kind of used cars. 759 00:39:28,080 --> 00:39:31,480 Speaker 1: So really Q four potentially is shaping up to to 760 00:39:31,560 --> 00:39:36,279 Speaker 1: see some lower core inflation. For instance, I'm going to 761 00:39:36,360 --> 00:39:38,480 Speaker 1: spike the football at the end of Q far well 762 00:39:38,520 --> 00:39:41,760 Speaker 1: Mer Sharif. Thank you so much for coming on. Fascinating conversation. 763 00:39:41,880 --> 00:39:44,759 Speaker 1: Always love chanting with you. Always learned something and we'll 764 00:39:44,880 --> 00:39:46,960 Speaker 1: have to have you back again to thank you. Take 765 00:39:47,000 --> 00:40:02,320 Speaker 1: care of Thanks. That was great. I love talking to 766 00:40:02,920 --> 00:40:04,799 Speaker 1: I always learned so much sitting as said, the fact 767 00:40:04,800 --> 00:40:06,839 Speaker 1: that he gave me, you know, the like throws, these 768 00:40:06,880 --> 00:40:09,440 Speaker 1: little like bits of red meat for team transitory. I 769 00:40:09,560 --> 00:40:11,360 Speaker 1: just actually like learning about this, Like I had no 770 00:40:11,440 --> 00:40:14,120 Speaker 1: idea how they captured health to church. That's so interesting 771 00:40:14,160 --> 00:40:17,040 Speaker 1: to me. Yeah, So I think I have maybe three 772 00:40:17,280 --> 00:40:22,160 Speaker 1: major takeaways from that. Like one, it's just crazy how 773 00:40:22,239 --> 00:40:24,880 Speaker 1: much of the market and our daily lives are linked 774 00:40:24,880 --> 00:40:27,920 Speaker 1: to the construction of this one index, and hat well't 775 00:40:28,000 --> 00:40:30,160 Speaker 1: I mean it's multiple indexes, but p p I c 776 00:40:30,360 --> 00:40:33,520 Speaker 1: p I and how it works, like think about all 777 00:40:33,520 --> 00:40:36,279 Speaker 1: the payments, Treasury link securities, things like that that are 778 00:40:36,400 --> 00:40:38,719 Speaker 1: linked to c p I, and so much of it 779 00:40:38,760 --> 00:40:42,160 Speaker 1: depends on the individual construction. And then the second takeaway, 780 00:40:42,280 --> 00:40:44,320 Speaker 1: you know what he was saying about the time lags 781 00:40:44,360 --> 00:40:47,200 Speaker 1: and how COVID kind of messed those up. I think 782 00:40:47,280 --> 00:40:49,160 Speaker 1: is a really good way of looking at why there's 783 00:40:49,200 --> 00:40:54,480 Speaker 1: been so much confusion over inflation. And Then thirdly, this 784 00:40:54,520 --> 00:40:57,799 Speaker 1: is something that I'd heard before, but the resource constraints 785 00:40:57,840 --> 00:41:00,360 Speaker 1: on the BLS in terms of a set bling some 786 00:41:00,440 --> 00:41:03,080 Speaker 1: of this data and trying to adjust it. I think 787 00:41:03,160 --> 00:41:06,239 Speaker 1: that is maybe an underappreciated factor over the past couple 788 00:41:06,239 --> 00:41:08,319 Speaker 1: of years. Well, and especially like some of these some 789 00:41:08,440 --> 00:41:11,520 Speaker 1: of the stickier prices within goods that like, of course 790 00:41:11,560 --> 00:41:13,759 Speaker 1: these should come down right, because we have every big 791 00:41:13,800 --> 00:41:17,160 Speaker 1: box retailer saying we have tons of inventory. The housing 792 00:41:17,200 --> 00:41:19,760 Speaker 1: markets slowed down, so it's like all kinds of reasons 793 00:41:19,800 --> 00:41:22,120 Speaker 1: to think, yeah, we should be seeing some deflation and furniture, 794 00:41:22,120 --> 00:41:24,080 Speaker 1: it's not happening. But then he says, oh, they you know, 795 00:41:24,239 --> 00:41:27,799 Speaker 1: maybe they only contract a couple of hundred in the survey. Well, right, 796 00:41:27,880 --> 00:41:31,040 Speaker 1: if your survey respondents are like the big box stores 797 00:41:31,080 --> 00:41:34,720 Speaker 1: that have pricing power, still have pricing power for a while, 798 00:41:34,840 --> 00:41:38,280 Speaker 1: then it'll be sticky. Now there's something, and we should 799 00:41:38,360 --> 00:41:42,000 Speaker 1: at some point do an episode on when they changed 800 00:41:42,360 --> 00:41:45,319 Speaker 1: the rules of inflation, because they look, it's crazy. I 801 00:41:45,360 --> 00:41:47,239 Speaker 1: think that, like, you know, forty years ago, if they 802 00:41:47,360 --> 00:41:51,520 Speaker 1: raised great that mathematically raised measured inflation because interest in 803 00:41:51,560 --> 00:41:54,120 Speaker 1: mortgages was including the CPI, which is also like kind 804 00:41:54,120 --> 00:41:56,040 Speaker 1: of maybe intuitive to a lot of people. Well, it's 805 00:41:56,080 --> 00:41:58,279 Speaker 1: one of those things like you can see why they 806 00:41:58,320 --> 00:42:00,480 Speaker 1: would do it, but on the other hand, it also 807 00:42:00,560 --> 00:42:03,200 Speaker 1: seems odd if you think that CPI is supposed to 808 00:42:03,239 --> 00:42:07,160 Speaker 1: measure the cost of living. Fascinating stuff. Yeah, we can 809 00:42:07,200 --> 00:42:08,759 Speaker 1: talk about this for a long time. Okay, shall we 810 00:42:08,800 --> 00:42:10,719 Speaker 1: leave it there. Let's leave it there. This has been 811 00:42:10,800 --> 00:42:13,800 Speaker 1: another episode of the All Thoughts podcast. I'm Tracy Alloway. 812 00:42:13,880 --> 00:42:16,360 Speaker 1: You can follow me on Twitter at Tracy Alloway and 813 00:42:16,400 --> 00:42:18,520 Speaker 1: I'm Joe wi Isn't All. You could follow me on 814 00:42:18,560 --> 00:42:22,160 Speaker 1: Twitter at the Stalwart. Follow our guest Omer Sharif He's 815 00:42:22,280 --> 00:42:25,360 Speaker 1: at f Cast of the Month. Follow our producer Carbin 816 00:42:25,480 --> 00:42:28,399 Speaker 1: Rodriguez at Kerman Armine, and check out all of our 817 00:42:28,440 --> 00:42:32,320 Speaker 1: podcasts Bloomberg under the handle at podcasts. Thanks for listening.