1 00:00:03,240 --> 00:00:07,560 Speaker 1: This is Masters in Business with Barry Ridholes on Bloomberg Radio. 2 00:00:08,080 --> 00:00:10,920 Speaker 1: This week on the podcast, I have an extra very 3 00:00:11,000 --> 00:00:15,280 Speaker 1: special guest. His name is Bill McBride. He is the 4 00:00:15,320 --> 00:00:21,040 Speaker 1: founder and runs the website Calculated Risk uh one of, 5 00:00:21,239 --> 00:00:25,000 Speaker 1: if not the best economic blogs out there, according to 6 00:00:25,040 --> 00:00:30,120 Speaker 1: pretty much everybody. So this was not my typical podcast 7 00:00:30,600 --> 00:00:33,520 Speaker 1: in the regular interview when I'm supposed to be doing 8 00:00:34,080 --> 00:00:38,240 Speaker 1: is asking questions and listening to what the guest responds, 9 00:00:38,560 --> 00:00:42,280 Speaker 1: and asking follow up questions and going uh huh uh huh. Yes. 10 00:00:42,840 --> 00:00:48,240 Speaker 1: But here's the thing. I know Bill since the first 11 00:00:48,320 --> 00:00:51,960 Speaker 1: day he started blogging, we were exchanging emails. I was 12 00:00:52,080 --> 00:00:56,280 Speaker 1: linking to him. I could I think I could honestly 13 00:00:56,320 --> 00:00:59,920 Speaker 1: say I linked to Calculator Risks before anybody had an 14 00:01:00,120 --> 00:01:03,680 Speaker 1: idea who they were. And um, I have been using 15 00:01:03,800 --> 00:01:07,160 Speaker 1: his research and his charts for the better part of 16 00:01:07,880 --> 00:01:12,280 Speaker 1: I don't know, ten eleven years, and we have always 17 00:01:12,600 --> 00:01:16,360 Speaker 1: had an email relationship. I think we had a couple 18 00:01:16,400 --> 00:01:21,200 Speaker 1: of telephone conversations, but I had never met Bill before 19 00:01:21,800 --> 00:01:25,040 Speaker 1: until the night before we recorded this podcast. We went 20 00:01:25,080 --> 00:01:29,240 Speaker 1: to dinner and I purposefully, with with eight people, I 21 00:01:29,319 --> 00:01:32,720 Speaker 1: purposely did not speak to Bill and told him, I'm 22 00:01:32,720 --> 00:01:34,200 Speaker 1: not going to talk to you until the two of 23 00:01:34,280 --> 00:01:37,800 Speaker 1: us are in the studio, And so this is supposed 24 00:01:37,840 --> 00:01:41,800 Speaker 1: to be an interview, but it's not. It's it's supposed 25 00:01:41,840 --> 00:01:47,040 Speaker 1: to be a podcast Q and A. But it really 26 00:01:47,280 --> 00:01:51,360 Speaker 1: is a genuine conversation between two people who know each 27 00:01:51,400 --> 00:01:54,280 Speaker 1: other for a decade and really have never sat down 28 00:01:54,320 --> 00:01:57,760 Speaker 1: and had a conversation before. So if you're looking for 29 00:01:57,800 --> 00:02:00,680 Speaker 1: the usual Q and A that that I try and 30 00:02:00,720 --> 00:02:04,080 Speaker 1: provide each week on the show, this isn't it. This 31 00:02:04,160 --> 00:02:06,520 Speaker 1: is me and Bill just shooting the breeze. It's two 32 00:02:06,520 --> 00:02:09,919 Speaker 1: guys who know and respect each other for a long time, 33 00:02:10,120 --> 00:02:15,280 Speaker 1: and I found it illuminating and fascinating. Um, there's probably 34 00:02:15,360 --> 00:02:18,359 Speaker 1: too much of me and it relative to what should be, 35 00:02:18,720 --> 00:02:22,079 Speaker 1: so I'll apologize for that in advance. But hey, if 36 00:02:22,120 --> 00:02:25,480 Speaker 1: you've ever known someone for what seems like forever but 37 00:02:25,639 --> 00:02:28,000 Speaker 1: never met them, when you finally get to meet them, 38 00:02:28,040 --> 00:02:31,120 Speaker 1: there's gonna be a lot of back and forth, and 39 00:02:31,520 --> 00:02:36,160 Speaker 1: truth be told, I thought the conversation was fascinating. I'm biased, 40 00:02:36,440 --> 00:02:39,200 Speaker 1: So let me stop babbling because you'll hear enough of 41 00:02:39,200 --> 00:02:43,160 Speaker 1: that throughout the rest of the interview with no further 42 00:02:43,200 --> 00:02:47,480 Speaker 1: Ado my two hour bull session with Bill McBride of 43 00:02:47,600 --> 00:02:54,840 Speaker 1: Calculated Risk. This is Masters in Business with Barry Ridholts 44 00:02:55,040 --> 00:02:58,760 Speaker 1: on Bloomberg Radio. I have a very special guest here 45 00:02:58,840 --> 00:03:02,359 Speaker 1: is somebody I have known for quite a long time. 46 00:03:02,800 --> 00:03:05,720 Speaker 1: Let me give you a quick background on Bill McBride, 47 00:03:05,800 --> 00:03:10,400 Speaker 1: who is the proprietor of Calculated Risk. He launched the 48 00:03:10,440 --> 00:03:14,120 Speaker 1: website in two thousand and five. The idea behind it 49 00:03:14,639 --> 00:03:20,000 Speaker 1: let's put simple opinion free analysis and charts about economic 50 00:03:20,080 --> 00:03:24,240 Speaker 1: data out in public where everyone can easily access it 51 00:03:24,320 --> 00:03:28,359 Speaker 1: and understand it. Uh. It has been called the best 52 00:03:28,520 --> 00:03:32,840 Speaker 1: of the economic blogs by such luminaries as Paul Krogman, 53 00:03:33,280 --> 00:03:36,960 Speaker 1: The Wall Street Journal, Business Week, Time. Pretty much everybody 54 00:03:37,000 --> 00:03:39,840 Speaker 1: puts the blog in its list of top twenty, or 55 00:03:39,880 --> 00:03:42,720 Speaker 1: Top fifty, or top one hundred or top ten blogs. 56 00:03:43,520 --> 00:03:48,280 Speaker 1: Bill's background is uh. He has an NBA from University 57 00:03:48,280 --> 00:03:54,040 Speaker 1: of California, Irvine, with a background in management, finance, and economics. 58 00:03:54,440 --> 00:03:57,640 Speaker 1: And he had been running a public company or involved 59 00:03:57,640 --> 00:04:01,560 Speaker 1: in a public company in the he retired and was 60 00:04:02,120 --> 00:04:05,480 Speaker 1: looking for something to do. UM. Bill McBride, welcome to 61 00:04:05,480 --> 00:04:08,400 Speaker 1: bloom Bark. Thanks for having me, Barry. Let's start with 62 00:04:08,520 --> 00:04:11,400 Speaker 1: your background so you're you're running a public company. You're 63 00:04:11,400 --> 00:04:14,400 Speaker 1: one of the co founders of a medical devices company, 64 00:04:14,440 --> 00:04:15,960 Speaker 1: is that right? That's correct. Yeah, I was the head 65 00:04:15,960 --> 00:04:17,960 Speaker 1: of R and D. So so tell us about this 66 00:04:18,040 --> 00:04:21,719 Speaker 1: what what was this company about? Ultimately it got sold 67 00:04:21,760 --> 00:04:24,920 Speaker 1: to a larger company. Yeah. Where we started in the eighties, 68 00:04:25,480 --> 00:04:29,560 Speaker 1: we were designing cardiac telemetry, which is it's it's like 69 00:04:29,600 --> 00:04:32,039 Speaker 1: a little box that you wear on you in the 70 00:04:32,080 --> 00:04:35,160 Speaker 1: hospital that connects the picks up your e c G 71 00:04:35,680 --> 00:04:37,719 Speaker 1: and sends it to a central monitor in the hospital. 72 00:04:37,760 --> 00:04:40,400 Speaker 1: It's for in hospital use. Did you have a background 73 00:04:40,440 --> 00:04:43,040 Speaker 1: in in medicine? I had. I had worked previously in 74 00:04:43,080 --> 00:04:46,799 Speaker 1: a telecommunications company, so it was more technology than medical. Yes, 75 00:04:46,880 --> 00:04:49,520 Speaker 1: and my mindergraduate grease and chemistry, so you know, it's 76 00:04:49,560 --> 00:04:52,200 Speaker 1: kind of a mix of things. And so what we 77 00:04:52,240 --> 00:04:55,960 Speaker 1: did is we um we kind of revolutionized that industry 78 00:04:56,000 --> 00:04:58,600 Speaker 1: because in the eighties was when everybody was making the 79 00:04:58,640 --> 00:05:01,520 Speaker 1: transition to digital in a out of different areas, and 80 00:05:01,560 --> 00:05:04,000 Speaker 1: we used some of the cell phone technology to make 81 00:05:04,000 --> 00:05:07,640 Speaker 1: the first digital cardiac telemetry. So so when someone gets 82 00:05:07,680 --> 00:05:12,120 Speaker 1: an e KG in a hospital or the monitoring UM, well, 83 00:05:12,200 --> 00:05:17,479 Speaker 1: you know, if you're in particular awards in the hospital, um, 84 00:05:17,640 --> 00:05:21,359 Speaker 1: postcardiac surgery. If they once they like to take you 85 00:05:21,400 --> 00:05:24,960 Speaker 1: off the bedside monitor and put you on a little 86 00:05:25,160 --> 00:05:27,760 Speaker 1: telemetry unit so you can get up and walk around 87 00:05:27,839 --> 00:05:30,479 Speaker 1: and still be monitored. And so that's the use for it. 88 00:05:30,680 --> 00:05:32,800 Speaker 1: There's other We also pick up other parameters in addition 89 00:05:32,839 --> 00:05:34,480 Speaker 1: to E c G and then we sent it back 90 00:05:34,480 --> 00:05:36,800 Speaker 1: to a central monitor with With that, then they can 91 00:05:36,839 --> 00:05:39,039 Speaker 1: have a nurses station, they can monitor the people walking 92 00:05:39,080 --> 00:05:41,960 Speaker 1: around the hospital. So what happened with this company in 93 00:05:42,000 --> 00:05:44,880 Speaker 1: the nineties, So well, we we we grew very quickly. 94 00:05:45,360 --> 00:05:49,280 Speaker 1: We we designed telemetry for most of the major medical 95 00:05:49,320 --> 00:05:51,960 Speaker 1: device companies. They started using ours under their own name, 96 00:05:52,440 --> 00:05:56,080 Speaker 1: and then uh we took it public in nine and 97 00:05:56,120 --> 00:06:00,200 Speaker 1: then sold it to ge Medical. And at that point 98 00:06:00,360 --> 00:06:04,799 Speaker 1: you are gainfully unemployed, that's correct, as one of the founders. 99 00:06:04,839 --> 00:06:09,040 Speaker 1: So the site launches in oh five. What led you 100 00:06:09,080 --> 00:06:13,160 Speaker 1: to say, I have an idea, let's analyze economic data. Well, 101 00:06:13,560 --> 00:06:16,200 Speaker 1: economics is always a hobby for me, and uh I 102 00:06:16,240 --> 00:06:18,080 Speaker 1: specialized that and when I got my m b A, 103 00:06:18,440 --> 00:06:22,599 Speaker 1: that was my focus. Um, you know I in the 104 00:06:22,600 --> 00:06:24,320 Speaker 1: early two thousands, I had a few things that I 105 00:06:24,360 --> 00:06:26,800 Speaker 1: was doing in two thousand four. I remember thinking, what 106 00:06:27,040 --> 00:06:29,119 Speaker 1: is a blog? And I think I stumbled across yours 107 00:06:29,120 --> 00:06:32,000 Speaker 1: said the big picture. Uh I if you remember Angry 108 00:06:32,000 --> 00:06:34,800 Speaker 1: Bear when it was rich the three PhD economists, and 109 00:06:34,880 --> 00:06:36,400 Speaker 1: so that kind of inspired me. I said, well, you 110 00:06:36,440 --> 00:06:38,120 Speaker 1: know what to really understand that, I'll just do one. 111 00:06:38,279 --> 00:06:40,240 Speaker 1: So I'll start a blog, but I'm not going to 112 00:06:40,320 --> 00:06:44,120 Speaker 1: write it about politics like most of the blogs I saw, 113 00:06:44,880 --> 00:06:47,880 Speaker 1: And what I want to focus on is housing because 114 00:06:48,040 --> 00:06:50,640 Speaker 1: of what I was seeing in southern California had just 115 00:06:50,880 --> 00:06:53,200 Speaker 1: gone off the rail. Yeah. You know, I was at 116 00:06:53,200 --> 00:06:55,760 Speaker 1: the gym one day and I was talking to this 117 00:06:55,920 --> 00:07:00,760 Speaker 1: attractive young lady who was a secretary for the Hurly 118 00:07:00,800 --> 00:07:05,920 Speaker 1: T shirt company. Oh sure, I know exact stuff. And 119 00:07:05,920 --> 00:07:08,200 Speaker 1: and uh, one day she came in and she goes, Bill, 120 00:07:08,240 --> 00:07:12,400 Speaker 1: I just bought a condo. Now this condo she bought, 121 00:07:12,440 --> 00:07:15,200 Speaker 1: she bought for four hundred and some thousand dollars. And 122 00:07:15,200 --> 00:07:16,800 Speaker 1: she had already told me she was making. She had 123 00:07:16,840 --> 00:07:19,320 Speaker 1: moved up. This is No. Four, This is a No. Four, 124 00:07:19,440 --> 00:07:21,760 Speaker 1: and she was she was probably making. You know, she 125 00:07:21,800 --> 00:07:24,640 Speaker 1: had had gotten up to about forty a year and income, 126 00:07:24,800 --> 00:07:29,160 Speaker 1: so forget the old rule of two times tend to 127 00:07:29,560 --> 00:07:32,760 Speaker 1: tend to one with no money down. And so after 128 00:07:32,840 --> 00:07:34,800 Speaker 1: she told me the story, I said, how can you 129 00:07:34,840 --> 00:07:36,720 Speaker 1: afford that? When she started telling me about the teaser 130 00:07:36,760 --> 00:07:38,400 Speaker 1: rate she had for the first year or two, and 131 00:07:38,480 --> 00:07:40,960 Speaker 1: I said, well, what happens when that that comes do? 132 00:07:41,560 --> 00:07:44,120 Speaker 1: And she goes, well, I'll just either you know, might 133 00:07:44,120 --> 00:07:47,040 Speaker 1: either I will have more income, or I'll sell the unit. 134 00:07:47,040 --> 00:07:48,560 Speaker 1: And I thought, well, she if this is happening all 135 00:07:48,600 --> 00:07:49,960 Speaker 1: over the place, there's gonna be no one to sell 136 00:07:50,000 --> 00:07:52,440 Speaker 1: it to. So I went home that day and started calling, 137 00:07:52,800 --> 00:07:55,000 Speaker 1: you know, some mortgage bankers I knew, and I said, 138 00:07:55,080 --> 00:07:58,040 Speaker 1: is this really possible? Oh yeah, you know, you don't 139 00:07:58,080 --> 00:08:00,240 Speaker 1: have to have you know anything, you know in um 140 00:08:00,800 --> 00:08:03,280 Speaker 1: you know the ninja loans, no income, no job, you know. 141 00:08:03,360 --> 00:08:05,920 Speaker 1: She she was, yeah, no, acid she was. She was 142 00:08:06,000 --> 00:08:10,800 Speaker 1: a great client, she had a job. Okay, So so 143 00:08:10,920 --> 00:08:15,880 Speaker 1: you launched the blog and you decided to do something 144 00:08:15,920 --> 00:08:21,280 Speaker 1: a little different than most blogs. Calculated Risk is fairly 145 00:08:21,680 --> 00:08:25,880 Speaker 1: opinion free every now and then, and it's much more 146 00:08:26,000 --> 00:08:29,040 Speaker 1: rare than the average blog. You'll come out and say 147 00:08:29,600 --> 00:08:32,120 Speaker 1: this is my opinion about X y Z. I mean, 148 00:08:32,320 --> 00:08:35,880 Speaker 1: that's like an annual event. Most of the time, you're 149 00:08:35,880 --> 00:08:39,240 Speaker 1: just saying, here's the data, Here's what it means. Why 150 00:08:39,280 --> 00:08:41,400 Speaker 1: get why do you know? I do slip in a 151 00:08:41,440 --> 00:08:43,640 Speaker 1: sentence or two here and there about what I think 152 00:08:43,840 --> 00:08:46,520 Speaker 1: is happening with that data. And then every once in 153 00:08:46,520 --> 00:08:50,160 Speaker 1: a while, I will, like you're saying, right, a overview 154 00:08:50,200 --> 00:08:52,040 Speaker 1: piece of where I think we are in the economy 155 00:08:52,080 --> 00:08:54,640 Speaker 1: and where we're going. You know, back in in two 156 00:08:54,640 --> 00:08:57,400 Speaker 1: thousand five, one of the things I focused on was, uh, 157 00:08:57,880 --> 00:09:00,800 Speaker 1: I was actually calling up regulators and asking them why 158 00:09:00,840 --> 00:09:03,120 Speaker 1: they're not doing anything? So I I, you know, I 159 00:09:03,200 --> 00:09:05,679 Speaker 1: and I would write about how which either regulators are 160 00:09:05,679 --> 00:09:08,960 Speaker 1: not doing their job and here's why I'm Barry Ridolts. 161 00:09:09,120 --> 00:09:12,640 Speaker 1: You're listening to Masters in Business on Bloomberg Radio. My 162 00:09:12,720 --> 00:09:16,720 Speaker 1: guests this week is Bill McBride. He is the founder 163 00:09:16,760 --> 00:09:22,080 Speaker 1: and chief author of the highly regarded economics blog Calculated Risk. 164 00:09:23,120 --> 00:09:27,400 Speaker 1: Let's jump right back into this. You've developed an expertise 165 00:09:27,440 --> 00:09:33,240 Speaker 1: in in mortgages and housing and real estate economics. Was 166 00:09:33,280 --> 00:09:35,480 Speaker 1: that something that you had done in a previous life 167 00:09:35,559 --> 00:09:38,520 Speaker 1: or is it just you gravitated it towards that because 168 00:09:38,520 --> 00:09:41,520 Speaker 1: you were in southern California and real estate in the 169 00:09:41,559 --> 00:09:44,560 Speaker 1: early two thousands had just gone insane in California. Well, 170 00:09:44,720 --> 00:09:46,840 Speaker 1: it really is a combination of things. My dad was 171 00:09:46,880 --> 00:09:48,880 Speaker 1: in real estate, and he was and he was a builder. 172 00:09:49,760 --> 00:09:51,800 Speaker 1: My mother was a real estate agent. So it was 173 00:09:51,800 --> 00:09:55,320 Speaker 1: always supper time conversation. Did you have that sort of 174 00:09:56,000 --> 00:09:58,800 Speaker 1: I at least saw what he was doing and chatted 175 00:09:58,840 --> 00:10:01,440 Speaker 1: with him about it. Uh, you know, after I started 176 00:10:01,480 --> 00:10:05,120 Speaker 1: my career, I was more science and technology oriented, but 177 00:10:05,600 --> 00:10:08,560 Speaker 1: I always have been interested in real estate. And so 178 00:10:08,960 --> 00:10:10,640 Speaker 1: you know, I mean I and and you know, I 179 00:10:10,640 --> 00:10:12,400 Speaker 1: had that a little bit of a background of what 180 00:10:12,520 --> 00:10:15,120 Speaker 1: they went through. And I saw my dad go through 181 00:10:15,240 --> 00:10:17,360 Speaker 1: the ups and downs. Where was he a builder? What 182 00:10:17,400 --> 00:10:19,840 Speaker 1: part of the country in down to San Diego? Ah, 183 00:10:19,920 --> 00:10:22,640 Speaker 1: So that was really an interesting and fast growing But 184 00:10:22,960 --> 00:10:26,000 Speaker 1: your dad was in the Navy. There's a huge naval 185 00:10:26,000 --> 00:10:28,000 Speaker 1: base since in fact, I think that's how we ended 186 00:10:28,040 --> 00:10:31,360 Speaker 1: up there. That makes sense, Cornado Island in that whole area, 187 00:10:31,920 --> 00:10:34,600 Speaker 1: So we went from the Navy to San Diego to 188 00:10:34,600 --> 00:10:37,959 Speaker 1: San Diego and housing. So post war that had to 189 00:10:38,000 --> 00:10:40,920 Speaker 1: be just a huge boom over there. Yeah, san Diego 190 00:10:41,000 --> 00:10:43,199 Speaker 1: was booming the whole time. I you know, when we 191 00:10:43,280 --> 00:10:45,400 Speaker 1: moved there when I was five, and so you know, 192 00:10:45,440 --> 00:10:47,480 Speaker 1: I was there until I went away to college. It 193 00:10:47,559 --> 00:10:50,840 Speaker 1: was boom time back in the it was the sixties 194 00:10:50,840 --> 00:10:55,280 Speaker 1: and seventies and and but even then there were big 195 00:10:55,280 --> 00:10:58,320 Speaker 1: waves cycles. Yes, you could you could see the ups 196 00:10:58,320 --> 00:11:00,319 Speaker 1: and downs. There were times when my dad was clearly 197 00:11:00,320 --> 00:11:04,000 Speaker 1: struggling financially, you know, elctially, my mom was a elementary 198 00:11:04,040 --> 00:11:07,760 Speaker 1: school principle, so she had a good, steady income. Uh 199 00:11:07,800 --> 00:11:10,360 Speaker 1: so they could offset each other. So so, how do 200 00:11:10,400 --> 00:11:14,680 Speaker 1: you respond to the comment that was everywhere back in 201 00:11:14,720 --> 00:11:17,960 Speaker 1: the early two thousand's, you know, we've never had a 202 00:11:18,000 --> 00:11:22,000 Speaker 1: downturn in the price of housing in the United States. Well, well, 203 00:11:22,040 --> 00:11:24,559 Speaker 1: first of all, that's not true. It's utterly false. There 204 00:11:24,559 --> 00:11:27,080 Speaker 1: have been repeated examples all the way back to the 205 00:11:27,080 --> 00:11:29,520 Speaker 1: Great Suppression. You know. One of the things is if 206 00:11:29,600 --> 00:11:31,560 Speaker 1: if you remember, I'm sure you do, back in two 207 00:11:31,640 --> 00:11:34,120 Speaker 1: thousand and five, is the data wasn't very good or 208 00:11:34,200 --> 00:11:37,360 Speaker 1: very available, especially on house prices. You know, we we 209 00:11:37,440 --> 00:11:40,400 Speaker 1: had the what's now the f h f A house 210 00:11:40,440 --> 00:11:42,960 Speaker 1: pricing decks just based on the Fannie and Freddie mortgages. 211 00:11:43,360 --> 00:11:45,960 Speaker 1: But we didn't have Case Shiller publicly available, or core 212 00:11:46,040 --> 00:11:48,839 Speaker 1: Logic public or several of the other you know, Zilo, 213 00:11:49,000 --> 00:11:51,640 Speaker 1: that was just that wasn't even somebody's thought yet, you know. 214 00:11:51,800 --> 00:11:54,560 Speaker 1: And so now we have so much better data, and 215 00:11:54,600 --> 00:11:57,080 Speaker 1: some of those guys case Shiller and core Logic have 216 00:11:57,720 --> 00:12:01,080 Speaker 1: published their data back to previous times, and you can't 217 00:12:01,080 --> 00:12:03,240 Speaker 1: see those ups and downs. And so the people that 218 00:12:03,280 --> 00:12:05,240 Speaker 1: were saying there were no ups and downs, there was 219 00:12:05,240 --> 00:12:08,199 Speaker 1: no real good data for them to make that argument. 220 00:12:08,480 --> 00:12:10,760 Speaker 1: And and obviously they had never lived in southern California, 221 00:12:10,760 --> 00:12:12,720 Speaker 1: because I had seen the ups and downs in the 222 00:12:12,760 --> 00:12:15,640 Speaker 1: house prices absolutely and and like there was a there 223 00:12:15,720 --> 00:12:18,640 Speaker 1: was a real boom in the eighties. House prices peaked 224 00:12:18,640 --> 00:12:21,800 Speaker 1: around nineteen nine in my area, and they slid all 225 00:12:21,840 --> 00:12:25,280 Speaker 1: the way to the same exact experience in New York 226 00:12:26,120 --> 00:12:29,800 Speaker 1: seven crash shakes Wall Street, a little bit alan Greenspan 227 00:12:30,000 --> 00:12:33,600 Speaker 1: cuts rates. You have a little bit of a surgeon 228 00:12:33,800 --> 00:12:36,680 Speaker 1: in real estate throughout the eighties, and then it rolled over. 229 00:12:36,679 --> 00:12:38,760 Speaker 1: If you bought a condo or co op in New 230 00:12:38,840 --> 00:12:42,160 Speaker 1: York in nine, you did not get back to break 231 00:12:42,240 --> 00:12:46,640 Speaker 1: even on that purchase price until plus or minus. And 232 00:12:46,640 --> 00:12:49,599 Speaker 1: you can see in the charts. But during the Great Depression, 233 00:12:50,040 --> 00:12:53,160 Speaker 1: we know real estate prices of course plummeted, and I 234 00:12:53,200 --> 00:12:55,800 Speaker 1: think it was someone at Columbia, I'm not positive did 235 00:12:55,800 --> 00:12:59,280 Speaker 1: a study on Manhattan real estate and they estimated that 236 00:12:59,320 --> 00:13:02,920 Speaker 1: real estate price has dropped sev during the Great Depression. 237 00:13:03,280 --> 00:13:05,840 Speaker 1: I mean, how do you just shrug that off in 238 00:13:05,920 --> 00:13:09,480 Speaker 1: your models? It's it's impossible. I never understood why people 239 00:13:09,600 --> 00:13:11,439 Speaker 1: say real estate prices I never go down. I never 240 00:13:11,480 --> 00:13:14,040 Speaker 1: understood it because there's there's plenty of evidence. Even though 241 00:13:14,080 --> 00:13:16,079 Speaker 1: we don't have the data that we have today, there 242 00:13:16,120 --> 00:13:19,200 Speaker 1: was still plenty of evidence. So so let's talk about 243 00:13:19,920 --> 00:13:23,200 Speaker 1: I've I've been using the charts and the information you 244 00:13:23,240 --> 00:13:26,480 Speaker 1: put on cafe thank you for for how long? I mean, 245 00:13:26,520 --> 00:13:31,840 Speaker 1: it's got to be at least a decade. And I 246 00:13:31,880 --> 00:13:34,400 Speaker 1: got into a fight with the Wall Street Journal about 247 00:13:35,080 --> 00:13:38,240 Speaker 1: it was I want to say, oh six or oh seven, 248 00:13:38,840 --> 00:13:41,880 Speaker 1: and they were doing the look real estate prices are improving, 249 00:13:42,600 --> 00:13:46,199 Speaker 1: and the response was, well, no, it's June. They oh, 250 00:13:46,320 --> 00:13:48,000 Speaker 1: you're looking at it month over month. You have to 251 00:13:48,040 --> 00:13:50,760 Speaker 1: look at it year over year. So I grabbed and 252 00:13:50,800 --> 00:13:52,480 Speaker 1: I brought a copy of it. I'll put it up 253 00:13:52,480 --> 00:13:56,560 Speaker 1: on the site. I grabbed your existing home sales year 254 00:13:56,600 --> 00:14:02,360 Speaker 1: over year by month that shows the same seasonality it right, 255 00:14:02,559 --> 00:14:06,040 Speaker 1: you know it it's at its nata in December and January, 256 00:14:06,120 --> 00:14:09,800 Speaker 1: it slowly rises throughout the spring, peeks later in the 257 00:14:09,800 --> 00:14:12,880 Speaker 1: fall and rolls off. You can't just look at June 258 00:14:13,000 --> 00:14:16,120 Speaker 1: versus February and say, oh, housing is fine. But that's 259 00:14:16,160 --> 00:14:18,640 Speaker 1: what a lot of media was doing. Yeah, you know, 260 00:14:18,880 --> 00:14:20,720 Speaker 1: I think that was one of the issues back in 261 00:14:20,760 --> 00:14:23,560 Speaker 1: two thousand and five was the media. I don't think 262 00:14:23,560 --> 00:14:26,080 Speaker 1: they really knew how to report housing. There was some 263 00:14:26,800 --> 00:14:29,160 Speaker 1: but to say that people missed it completely is wrong. 264 00:14:29,200 --> 00:14:31,680 Speaker 1: There were some excellent articles, for sure, and and there 265 00:14:31,680 --> 00:14:36,280 Speaker 1: were some award winning articles. And and give us David Strettfield, 266 00:14:36,480 --> 00:14:38,000 Speaker 1: who was at the l A Times at the time, 267 00:14:38,040 --> 00:14:40,440 Speaker 1: now he's in New York Times. He won awards for 268 00:14:40,520 --> 00:14:43,840 Speaker 1: his housing articles. They were excellent. And uh, you know, 269 00:14:44,040 --> 00:14:46,360 Speaker 1: I mean so so there were there were plenty of 270 00:14:46,400 --> 00:14:48,640 Speaker 1: good articles, but I think they got lost in the 271 00:14:48,640 --> 00:14:50,640 Speaker 1: bad articles. And and you know, and you know how 272 00:14:50,680 --> 00:14:54,400 Speaker 1: the balance media works in classic false equivalent. If you 273 00:14:54,520 --> 00:14:57,160 Speaker 1: if you, if you talk to somebody who was very 274 00:14:57,200 --> 00:14:59,240 Speaker 1: concerned about housing, it could make a good argument on 275 00:14:59,280 --> 00:15:02,800 Speaker 1: the making mortgages. They would always go talk to somebody 276 00:15:03,040 --> 00:15:06,160 Speaker 1: who was impressive background who would say they own house 277 00:15:06,200 --> 00:15:09,080 Speaker 1: prices never go down. Uh, there's nothing to worry about, 278 00:15:09,160 --> 00:15:12,360 Speaker 1: you know. And and so I think for the average 279 00:15:12,400 --> 00:15:15,240 Speaker 1: person who was getting their information that way, it was 280 00:15:15,320 --> 00:15:17,800 Speaker 1: difficult to see that there was a problem. Now. I 281 00:15:17,880 --> 00:15:20,000 Speaker 1: run into people all the time to say, you know, 282 00:15:20,040 --> 00:15:22,920 Speaker 1: I thought there was something really wrong. So most people 283 00:15:23,160 --> 00:15:25,520 Speaker 1: in the back of their minds, especially people in areas 284 00:15:25,600 --> 00:15:30,760 Speaker 1: like you know, southern California, Florida, you know, Nevada, they 285 00:15:30,800 --> 00:15:33,120 Speaker 1: were thinking, I think a lot of people are going 286 00:15:33,160 --> 00:15:35,960 Speaker 1: there's something wrong here. How much of that is hindsight 287 00:15:36,040 --> 00:15:38,680 Speaker 1: bias where but by the way, it could be. You 288 00:15:38,840 --> 00:15:44,200 Speaker 1: recall the number of people legitimately in prints in a 289 00:15:44,360 --> 00:15:48,760 Speaker 1: verifiable way warning about housing prices. There were a handful 290 00:15:48,800 --> 00:15:51,600 Speaker 1: of people, a handful of us. You were one, well, 291 00:15:51,640 --> 00:15:53,640 Speaker 1: you me, you know, I, I know a few other 292 00:15:53,680 --> 00:15:56,520 Speaker 1: people they were doing it. But now every person I met, Oh, 293 00:15:56,560 --> 00:16:00,280 Speaker 1: of course I knew the housing crisis was about to collapse. Well, well, 294 00:16:00,320 --> 00:16:02,600 Speaker 1: I just I just looked at certain data and said, 295 00:16:02,960 --> 00:16:07,120 Speaker 1: this ratio which has been consistent home price to meeting income, 296 00:16:07,520 --> 00:16:10,760 Speaker 1: the cost of renting versus cost of owning. You covered 297 00:16:10,800 --> 00:16:13,800 Speaker 1: a ton of this stuff how how frustrating was it 298 00:16:14,080 --> 00:16:17,360 Speaker 1: when you saw the train wreck coming, but you couldn't 299 00:16:17,360 --> 00:16:20,640 Speaker 1: really convince the average person that hey, something wicked this 300 00:16:20,680 --> 00:16:23,960 Speaker 1: way comes. Well, you know, I I was really focused 301 00:16:24,000 --> 00:16:27,320 Speaker 1: on trying to to to get the regulators to pay 302 00:16:27,360 --> 00:16:30,360 Speaker 1: attention to it, and and that was a very frustrating 303 00:16:30,400 --> 00:16:33,840 Speaker 1: process because they because they were paying attention to it, 304 00:16:34,120 --> 00:16:37,320 Speaker 1: but they couldn't do anything. Their hands were tied. And uh, 305 00:16:37,440 --> 00:16:39,560 Speaker 1: you know, the the regular person. Uh, you know, I 306 00:16:39,600 --> 00:16:42,320 Speaker 1: started my blog, I was writing. I was writing for 307 00:16:42,400 --> 00:16:46,440 Speaker 1: friends and relatives, you know, so I was mostly just saying, hey, 308 00:16:46,600 --> 00:16:48,920 Speaker 1: you know, if they asked me, I would tell them 309 00:16:48,960 --> 00:16:53,000 Speaker 1: don't buy please, don't buy anything. You know. Uh you 310 00:16:53,000 --> 00:16:55,080 Speaker 1: know it's but you know, you put a blog out 311 00:16:55,120 --> 00:16:56,760 Speaker 1: there in public, and so all of a sudden people 312 00:16:56,800 --> 00:16:59,920 Speaker 1: start reading it. I'm very hults you're listening to mass 313 00:17:00,120 --> 00:17:03,000 Speaker 1: was in Business on Bloomberg Radio. My special guest this 314 00:17:03,040 --> 00:17:06,280 Speaker 1: week is Bill McBride. He is the founder of the 315 00:17:06,359 --> 00:17:11,480 Speaker 1: Calculated Risk website, lauded by everyone from Business Week, Wall 316 00:17:11,480 --> 00:17:14,639 Speaker 1: Street Journal, uh New York Times as the single best 317 00:17:14,720 --> 00:17:19,280 Speaker 1: economics blog there is. Um I put out a request 318 00:17:19,400 --> 00:17:22,040 Speaker 1: on the Big Picture as well as on Twitter uh, 319 00:17:22,080 --> 00:17:25,000 Speaker 1: if any of your readers had questions for you, and 320 00:17:25,040 --> 00:17:27,760 Speaker 1: I got a long list of stuff, let's let's jump 321 00:17:27,840 --> 00:17:29,399 Speaker 1: into some of them. I think some of these are 322 00:17:29,440 --> 00:17:34,200 Speaker 1: really interesting. First question, you're one of the few bloggers 323 00:17:34,200 --> 00:17:38,199 Speaker 1: who still maintains a comments section, and it's a mess. Sorry, 324 00:17:38,240 --> 00:17:43,199 Speaker 1: but I think that's honest. Why maintain comments? That's a 325 00:17:43,200 --> 00:17:48,240 Speaker 1: great question. And and uh, you know, comments early in 326 00:17:48,440 --> 00:17:53,440 Speaker 1: the blog were unbelievably outstanding, amazing. As a matter of fact, 327 00:17:53,440 --> 00:17:55,320 Speaker 1: I thought the comments, who are one of the key 328 00:17:55,359 --> 00:17:59,639 Speaker 1: elements to the blog. The comments turned more into just 329 00:17:59,760 --> 00:18:06,560 Speaker 1: a at session about unrelated information, off topic, trolls, spam, 330 00:18:06,880 --> 00:18:09,520 Speaker 1: it's gone off the right. Yeah, well you know, NPR, 331 00:18:09,600 --> 00:18:12,080 Speaker 1: by the way, just killed their common sense. You know. 332 00:18:12,119 --> 00:18:15,439 Speaker 1: We we do have a comment section where people have 333 00:18:15,520 --> 00:18:19,840 Speaker 1: to register so that you can't just get the drive 334 00:18:19,920 --> 00:18:24,120 Speaker 1: by commentors, so the trolling goes down, but the it's 335 00:18:24,200 --> 00:18:27,920 Speaker 1: it's basically off topic most of the time. BuzzFeed does 336 00:18:27,960 --> 00:18:30,719 Speaker 1: this thing now where you can comment, but only if 337 00:18:30,720 --> 00:18:34,040 Speaker 1: you register through Facebook, which is your real identity, so 338 00:18:34,160 --> 00:18:36,919 Speaker 1: you lose a lot of the really off the change. 339 00:18:37,080 --> 00:18:41,280 Speaker 1: But the racist nonsense, yeah, you know, the they and 340 00:18:41,320 --> 00:18:43,959 Speaker 1: we don't have that for the most part. And you know, 341 00:18:44,359 --> 00:18:47,080 Speaker 1: those people that are racists are bigoted in some way. 342 00:18:47,119 --> 00:18:51,240 Speaker 1: We've tried to band but the I keep it because 343 00:18:51,240 --> 00:18:54,159 Speaker 1: a lot of the old timers are still there, but 344 00:18:54,240 --> 00:18:57,080 Speaker 1: they chat more than they more than the economic content, 345 00:18:57,119 --> 00:18:59,720 Speaker 1: and they're kind of friends so they so, you know, 346 00:18:59,760 --> 00:19:02,600 Speaker 1: I just I leave it for them. If people don't 347 00:19:02,640 --> 00:19:05,000 Speaker 1: like the comments, then don't don't participation, don't read the 348 00:19:05,000 --> 00:19:08,399 Speaker 1: comments exactly. That's my view. And I if there's you know, 349 00:19:08,440 --> 00:19:11,800 Speaker 1: if there's ever you know, the anti semetic things I 350 00:19:11,920 --> 00:19:14,439 Speaker 1: banned so many people, well, it gets to be a 351 00:19:14,480 --> 00:19:19,400 Speaker 1: giant curation time sockets complicated. I had some people write 352 00:19:19,440 --> 00:19:21,720 Speaker 1: me when I killed comments on the Big Picture, which 353 00:19:21,760 --> 00:19:26,159 Speaker 1: is years ago. Um, well thanks for the site, but 354 00:19:26,280 --> 00:19:28,639 Speaker 1: I'm done. If you don't have comments, you know, you 355 00:19:28,800 --> 00:19:31,520 Speaker 1: understand how many hours a week it is to maintain 356 00:19:31,560 --> 00:19:35,680 Speaker 1: the comments, and you guys don't see the really horrific comments, 357 00:19:35,720 --> 00:19:38,480 Speaker 1: and it just got to be a total dreg But 358 00:19:38,640 --> 00:19:40,880 Speaker 1: that was a lost era. I thought the comments were 359 00:19:40,920 --> 00:19:44,760 Speaker 1: fantastic on you could read a really interesting article and 360 00:19:44,800 --> 00:19:48,520 Speaker 1: then spend a half hour reading some really smart, insightful 361 00:19:48,600 --> 00:19:51,520 Speaker 1: feedback on that audit there. Well, you know. I'm sure 362 00:19:51,800 --> 00:19:53,800 Speaker 1: some of your commenters are asked you any many of 363 00:19:53,840 --> 00:19:56,280 Speaker 1: mine were, Uh, one of the one of the I'm 364 00:19:56,320 --> 00:19:58,760 Speaker 1: sure we're going to talk about my code blogger, Tanta. 365 00:19:58,800 --> 00:20:02,480 Speaker 1: At some point I met Tanta through the comments. Yeah. 366 00:20:02,520 --> 00:20:06,360 Speaker 1: She she showed up and was commenting, and every time 367 00:20:06,520 --> 00:20:08,240 Speaker 1: she would either correct something I had said. If I 368 00:20:08,280 --> 00:20:11,560 Speaker 1: said something about the mortgage industry, and I would call 369 00:20:11,600 --> 00:20:13,680 Speaker 1: it my mortgage banker friends, and they go, oh, yeah, 370 00:20:13,680 --> 00:20:16,639 Speaker 1: she's right, all right, So I instantly corrected on my 371 00:20:16,640 --> 00:20:19,960 Speaker 1: blog and I'd credit Tanta and and uh, or she 372 00:20:20,000 --> 00:20:22,119 Speaker 1: would say, hey, yeah, that's you know. She she was 373 00:20:22,160 --> 00:20:25,119 Speaker 1: really sharp, she knew everything, and she was very quick witted. 374 00:20:25,359 --> 00:20:27,679 Speaker 1: And so that's how I actually got to know my 375 00:20:27,760 --> 00:20:30,360 Speaker 1: code blogger. Through the comments. That's where I met her. 376 00:20:30,480 --> 00:20:33,199 Speaker 1: So so let's talk about that she starts writing for you, 377 00:20:33,400 --> 00:20:37,160 Speaker 1: and well she this is what happened, and she commented 378 00:20:37,160 --> 00:20:40,720 Speaker 1: a lot in two thousand five. In two thousand six, 379 00:20:40,760 --> 00:20:44,640 Speaker 1: she disappeared from the comments. About six months later, she 380 00:20:44,840 --> 00:20:49,359 Speaker 1: reappeared and she told me that she had been diagnosed 381 00:20:49,400 --> 00:20:54,200 Speaker 1: with stage four ovarian cancer, had had left her job, uh, 382 00:20:54,240 --> 00:20:56,800 Speaker 1: and she had stopped commenting because she wasn't able to 383 00:20:56,960 --> 00:20:58,520 Speaker 1: and she didn't even think she was going to live 384 00:20:59,240 --> 00:21:02,040 Speaker 1: and so uh, I then asked her, well, why don't 385 00:21:02,040 --> 00:21:04,719 Speaker 1: you come and write for the blog if you're not working, 386 00:21:04,920 --> 00:21:08,000 Speaker 1: because she's working in the mortgage industry, and uh, and 387 00:21:08,240 --> 00:21:10,520 Speaker 1: it took me a little convincing, but she started in 388 00:21:10,960 --> 00:21:13,560 Speaker 1: I think her first post was in December two thousand six, 389 00:21:14,440 --> 00:21:17,199 Speaker 1: and almost two years before she passed away. So she 390 00:21:17,320 --> 00:21:18,960 Speaker 1: was a regular on the side for a while, but 391 00:21:19,040 --> 00:21:22,040 Speaker 1: and ultimately succumbed to the illness. Yes, but you know, 392 00:21:22,080 --> 00:21:26,480 Speaker 1: she was stunning before she started writing for the blog. 393 00:21:26,560 --> 00:21:30,240 Speaker 1: I probably wrote longer pieces. And then when she showed up, 394 00:21:31,000 --> 00:21:35,680 Speaker 1: she undergraduate Greems in literature. Her pieces were brilliant. Uh, 395 00:21:36,000 --> 00:21:38,400 Speaker 1: they were they they One of her goals, she said, 396 00:21:38,440 --> 00:21:41,359 Speaker 1: was to make blogs entries could be long and still 397 00:21:41,440 --> 00:21:45,520 Speaker 1: well read. And she accomplished. Uh. She would explain mortgage 398 00:21:46,000 --> 00:21:49,320 Speaker 1: uh issues in complete detail and all that stuff still 399 00:21:49,359 --> 00:21:52,680 Speaker 1: on the blog. Um. And you know, people from the 400 00:21:52,720 --> 00:21:55,800 Speaker 1: Federal Reserve were crediting her and in papers they were 401 00:21:55,840 --> 00:21:58,960 Speaker 1: writing because they were learning from her too. And you know, 402 00:21:59,080 --> 00:22:02,600 Speaker 1: she was real mortgage banker. She knew the banking, the 403 00:22:02,600 --> 00:22:05,320 Speaker 1: mortgage banking industry inside and out. You know, she was 404 00:22:05,359 --> 00:22:09,200 Speaker 1: absolutely terrified and and and she was scared because they 405 00:22:09,200 --> 00:22:12,320 Speaker 1: were they were all the mortgage industry was pulling back 406 00:22:12,359 --> 00:22:16,160 Speaker 1: on the risk management sign and his money to be made, yeah, 407 00:22:16,160 --> 00:22:18,719 Speaker 1: and worry about risk later, oh yeah. And and and you know, 408 00:22:18,800 --> 00:22:21,520 Speaker 1: and in the in the whole industry changed. They went 409 00:22:21,560 --> 00:22:24,200 Speaker 1: away from the three c's. You know, where you're you're 410 00:22:24,200 --> 00:22:27,600 Speaker 1: looking at credit and collateral and capacity to pay. And 411 00:22:27,640 --> 00:22:30,320 Speaker 1: we just went to FICO scores. I'm Barry Ridhults. You're 412 00:22:30,400 --> 00:22:33,960 Speaker 1: listening to Masters in Business on Bloomberg Radio. My guest 413 00:22:34,000 --> 00:22:37,760 Speaker 1: today is Bill McBride. He is the founder and proprietor 414 00:22:37,960 --> 00:22:43,240 Speaker 1: of the highly rated Calculated Risk Economics blog, well regarded 415 00:22:43,280 --> 00:22:47,399 Speaker 1: by many people. You don't have a PhD in economics, 416 00:22:47,440 --> 00:22:49,320 Speaker 1: you don't have a you have an m b A. 417 00:22:50,560 --> 00:22:55,080 Speaker 1: How did you go from essentially a medical devices h 418 00:22:55,200 --> 00:22:58,760 Speaker 1: company founder to one of the leading lights in in 419 00:22:59,200 --> 00:23:03,080 Speaker 1: financial economics writing well, I don't I don't know if 420 00:23:03,119 --> 00:23:05,520 Speaker 1: I'm a leading light, but but it's very nice all 421 00:23:05,560 --> 00:23:07,439 Speaker 1: those things people have said about me. But you know, 422 00:23:07,480 --> 00:23:10,200 Speaker 1: I I I've had always had an interest in economics. 423 00:23:10,240 --> 00:23:13,560 Speaker 1: I've always had an interest in housing. I study hard. 424 00:23:14,480 --> 00:23:17,800 Speaker 1: I I dig hard to try to understand the data. 425 00:23:18,400 --> 00:23:21,159 Speaker 1: And uh, and I've a lot I've worked with a 426 00:23:21,160 --> 00:23:24,160 Speaker 1: lot of economists since I started the blog, a lot 427 00:23:24,160 --> 00:23:28,120 Speaker 1: of economic academic economists that that I call friends. Now 428 00:23:28,200 --> 00:23:32,800 Speaker 1: give us some names, Jim Hamilton's down fantastic, Mark Toma 429 00:23:32,960 --> 00:23:36,920 Speaker 1: up in North another one, Tim Dewey. Sure, so you're 430 00:23:37,000 --> 00:23:41,240 Speaker 1: you're just named my starting lineup of that economists, right, Yeah? Yeah, 431 00:23:41,240 --> 00:23:43,679 Speaker 1: I mean so so, uh, you know those guys I 432 00:23:43,760 --> 00:23:46,560 Speaker 1: chat with, I chat with several of them all the time, 433 00:23:47,160 --> 00:23:51,240 Speaker 1: and uh, and you know, it's it's so it helps 434 00:23:51,280 --> 00:23:54,480 Speaker 1: me focus on what on what's important in economics and 435 00:23:54,520 --> 00:23:57,360 Speaker 1: how to understand it. And and I think they liked 436 00:23:57,359 --> 00:24:00,280 Speaker 1: that I really dig through the data and and so 437 00:24:00,320 --> 00:24:02,960 Speaker 1: it's kind of a mutual thing. So, so let's talk 438 00:24:03,000 --> 00:24:05,359 Speaker 1: a little bit about the state of the U. S. Economy. 439 00:24:05,680 --> 00:24:08,680 Speaker 1: I'm going to throw some things out that I hear 440 00:24:08,720 --> 00:24:15,280 Speaker 1: and see and read online that I question pretty um significantly. 441 00:24:15,320 --> 00:24:17,560 Speaker 1: And I want to just get your your feedback on 442 00:24:17,600 --> 00:24:21,600 Speaker 1: each of these. Um. You know, the recession never ended, 443 00:24:21,640 --> 00:24:25,040 Speaker 1: the economy is still spiraling downward, and we're going into 444 00:24:25,040 --> 00:24:29,760 Speaker 1: a depression. Well that's that's that's unrealistic obviously. UM. I 445 00:24:29,800 --> 00:24:35,080 Speaker 1: mean employment is up substantially since two thousand nine. Um, 446 00:24:35,119 --> 00:24:38,520 Speaker 1: the you know, the economy is growing slowly from a 447 00:24:38,560 --> 00:24:43,080 Speaker 1: GDP perspective. Uh. That's driven in my view by two 448 00:24:43,080 --> 00:24:47,080 Speaker 1: main things. One is, for some reason, productivities down, um, 449 00:24:47,320 --> 00:24:49,879 Speaker 1: something that I don't think anybody can really control, at 450 00:24:49,920 --> 00:24:53,479 Speaker 1: least measure productivity, right. But also and a key thing 451 00:24:53,520 --> 00:24:57,440 Speaker 1: that's very rarely mentioned is demographics. We've we've the prime 452 00:24:57,520 --> 00:25:02,240 Speaker 1: working age population started decreasing, not not workforce but population 453 00:25:02,320 --> 00:25:05,240 Speaker 1: in about two thousand and ten and decrease for five 454 00:25:05,320 --> 00:25:07,280 Speaker 1: or six years. And that's because of all the baby boomers. 455 00:25:07,680 --> 00:25:09,760 Speaker 1: So if you were born in the fifties or sixties, 456 00:25:10,119 --> 00:25:13,160 Speaker 1: so let's say you're born in nineteen fifty, that would 457 00:25:13,160 --> 00:25:16,800 Speaker 1: make you sixty six today, you're you're thinking about retiring, right, 458 00:25:16,840 --> 00:25:18,840 Speaker 1: and you're out of the prime working age. You know, 459 00:25:18,920 --> 00:25:21,800 Speaker 1: when as you get past sixty, which I can say 460 00:25:21,920 --> 00:25:25,320 Speaker 1: is happens you you you have less energy, you know, 461 00:25:25,359 --> 00:25:27,720 Speaker 1: So are you're speaking personally? You know? Yeah, you know 462 00:25:27,760 --> 00:25:30,120 Speaker 1: I'm t talking about myself. So so you know, when 463 00:25:30,200 --> 00:25:32,600 Speaker 1: when you get a little older, you you know, I'm 464 00:25:32,600 --> 00:25:35,960 Speaker 1: still doing things, but uh, yeah, I don't think I'm 465 00:25:36,000 --> 00:25:39,840 Speaker 1: as excited about spending a lot of hours a day working, 466 00:25:40,320 --> 00:25:42,920 Speaker 1: but you do spend a decent amount of I spend 467 00:25:42,920 --> 00:25:45,399 Speaker 1: a decent amount, nothing like what I was spending in 468 00:25:45,400 --> 00:25:48,360 Speaker 1: two thousand nine. But that's that's not age related, that's 469 00:25:48,400 --> 00:25:51,800 Speaker 1: just crisis crisis related. Yeah, you've got to be doing two, three, 470 00:25:51,920 --> 00:25:54,960 Speaker 1: four hours a day. Yes, oh yeah, at least you're 471 00:25:55,040 --> 00:25:59,879 Speaker 1: what my wife describes as gainfully unemployed. Right, It's like 472 00:26:00,040 --> 00:26:01,840 Speaker 1: you would be doing this whether there was money in 473 00:26:01,920 --> 00:26:05,040 Speaker 1: it or not. And h is there money in it? 474 00:26:05,160 --> 00:26:07,920 Speaker 1: That's a question that people ask, well, what is there 475 00:26:07,920 --> 00:26:10,159 Speaker 1: money and blogging? Well, first of all, when I started 476 00:26:10,160 --> 00:26:12,359 Speaker 1: the blog, I didn't take any advertising. For two or 477 00:26:12,400 --> 00:26:14,919 Speaker 1: three years, I didn't even think about it, so it 478 00:26:14,960 --> 00:26:18,719 Speaker 1: really was just a hobby. People said, hey, take advertising, 479 00:26:18,760 --> 00:26:22,200 Speaker 1: and so I eventually did. Uh. There's not a whole 480 00:26:22,200 --> 00:26:25,240 Speaker 1: lot of money in it, but but you know, there's 481 00:26:25,280 --> 00:26:27,880 Speaker 1: pays for some nice dinners out there you go. So 482 00:26:28,080 --> 00:26:30,199 Speaker 1: so it's still more or less a hobby that that 483 00:26:30,280 --> 00:26:33,679 Speaker 1: keeps you Uh yeah, active, Yes, you know. I I 484 00:26:33,680 --> 00:26:36,520 Speaker 1: guess I have this thing. I promise my readers that 485 00:26:36,640 --> 00:26:39,760 Speaker 1: I would call our try to call the next recession, 486 00:26:40,320 --> 00:26:42,800 Speaker 1: I said, And you've been pretty consistent saying we're knowing 487 00:26:42,880 --> 00:26:45,840 Speaker 1: your recession anytime. Yeah, So I I'm gonna say I 488 00:26:45,840 --> 00:26:48,080 Speaker 1: I hope to hang around long enough to do that, 489 00:26:48,880 --> 00:26:50,680 Speaker 1: and I don't see one in the near term at all, 490 00:26:50,720 --> 00:26:52,160 Speaker 1: So I guess I'm gonna be around for a while. 491 00:26:52,240 --> 00:26:54,719 Speaker 1: Let let's look at the indicators that you track in 492 00:26:54,800 --> 00:26:59,280 Speaker 1: order to identify a recession. And you track everything from 493 00:26:59,600 --> 00:27:04,000 Speaker 1: rail car waitings to two ships coming into the l 494 00:27:04,080 --> 00:27:07,479 Speaker 1: A port. It's not just GDP employment. You look at 495 00:27:07,480 --> 00:27:10,000 Speaker 1: it a ton of stuff. What what are some of 496 00:27:10,040 --> 00:27:14,760 Speaker 1: your favorite indicators to look at? Well? To me, the housing, 497 00:27:15,880 --> 00:27:19,760 Speaker 1: new home sales, housing starts. I always start there. You 498 00:27:19,800 --> 00:27:22,520 Speaker 1: know employment, of course, it's the big big dogs, right, 499 00:27:22,720 --> 00:27:25,280 Speaker 1: So I mean employment went negative for several months in 500 00:27:25,280 --> 00:27:27,440 Speaker 1: a row. I would really be Now. I heard from 501 00:27:27,480 --> 00:27:32,080 Speaker 1: some political candidate that all of the employment data is fake. Well, 502 00:27:32,160 --> 00:27:34,920 Speaker 1: I I think I don't think there's probably a better 503 00:27:35,000 --> 00:27:37,760 Speaker 1: organization than the b l S as far as telling 504 00:27:37,880 --> 00:27:41,600 Speaker 1: us being transparent on how they do their work. They 505 00:27:41,760 --> 00:27:45,439 Speaker 1: publicly announced all the changes. It's always you think pademically driven. 506 00:27:45,520 --> 00:27:48,119 Speaker 1: You can go to their website, you can understand exactly 507 00:27:48,200 --> 00:27:51,639 Speaker 1: what they do, what they don't do, and and how 508 00:27:51,720 --> 00:27:54,520 Speaker 1: any changes which have been minor over the years in 509 00:27:54,640 --> 00:27:59,720 Speaker 1: how they gather data. Uh, so they're completely transparent and 510 00:27:59,760 --> 00:28:01,760 Speaker 1: you call them up and ask them question. Yeah, and 511 00:28:01,760 --> 00:28:04,119 Speaker 1: they're and they're very they're very helpful. So the the 512 00:28:04,320 --> 00:28:08,760 Speaker 1: the it's possible to disagree that, oh there there's a 513 00:28:08,800 --> 00:28:11,359 Speaker 1: different way to measure it, but to say that they're 514 00:28:11,359 --> 00:28:15,679 Speaker 1: doing it fake is outrageous. And there's outrageous. Yeah, this 515 00:28:15,800 --> 00:28:20,800 Speaker 1: was what three thousand statisticians, PhD s, economists, etcetera. Could 516 00:28:20,840 --> 00:28:24,320 Speaker 1: you really fake something and not have that leak out somewhere? 517 00:28:24,520 --> 00:28:27,760 Speaker 1: They're not all from one party or the other. It 518 00:28:27,840 --> 00:28:31,400 Speaker 1: seems like an impossible claim. It is. It is impossible, 519 00:28:31,480 --> 00:28:35,760 Speaker 1: and and there are independent ways to measure some of 520 00:28:35,800 --> 00:28:38,600 Speaker 1: that and and and it looks good too. You know, 521 00:28:38,960 --> 00:28:41,600 Speaker 1: whether you look at a dB employment, which is a 522 00:28:41,640 --> 00:28:45,360 Speaker 1: private measure, they're on it. Also, they're they're part of 523 00:28:45,360 --> 00:28:48,680 Speaker 1: the part of the conspiracy. That's the always the answer, 524 00:28:48,720 --> 00:28:51,959 Speaker 1: you get it. Those those numbers are very very good 525 00:28:52,040 --> 00:28:55,320 Speaker 1: and and uh, you know, do they describe everything? No, 526 00:28:55,680 --> 00:28:58,120 Speaker 1: the model isn't perfect by any stretch. But but but 527 00:28:58,200 --> 00:29:00,640 Speaker 1: the but the methodology is transparent. It so you can 528 00:29:00,760 --> 00:29:03,400 Speaker 1: go in and it's the same as like new home 529 00:29:03,440 --> 00:29:06,240 Speaker 1: sales or housing starts. You can go and see what 530 00:29:06,320 --> 00:29:08,600 Speaker 1: they count, what they don't count, you know, how they 531 00:29:08,680 --> 00:29:12,200 Speaker 1: add them in. Uh. You know that was very important 532 00:29:12,320 --> 00:29:15,320 Speaker 1: during the crisis because you had to see you had 533 00:29:15,320 --> 00:29:17,280 Speaker 1: to see, like a new home sales, how they canceled 534 00:29:17,960 --> 00:29:20,920 Speaker 1: you know, they handled canceled contract was a whole separate Yeah, 535 00:29:20,920 --> 00:29:23,720 Speaker 1: and they handle the completely different than the public companies. 536 00:29:23,800 --> 00:29:26,080 Speaker 1: So and so you could you could kind of say, well, gee, 537 00:29:26,120 --> 00:29:27,480 Speaker 1: you know they're going to catch up on this and 538 00:29:27,480 --> 00:29:30,960 Speaker 1: they're following and uh, you know, the public companies basically 539 00:29:30,960 --> 00:29:33,760 Speaker 1: have to here's what here's what we got there reporting 540 00:29:33,840 --> 00:29:39,000 Speaker 1: net sales where the UH Census Bureaus tracking a house 541 00:29:39,200 --> 00:29:41,000 Speaker 1: and then if it gets canceled later, then they take 542 00:29:41,040 --> 00:29:44,000 Speaker 1: it out. So it's it's uh, but those sales that 543 00:29:44,040 --> 00:29:47,080 Speaker 1: they originally reported is still there. It's kind of it's 544 00:29:47,080 --> 00:29:49,800 Speaker 1: so it's's important to understand that methodology right now that 545 00:29:49,920 --> 00:29:54,960 Speaker 1: that's irrelevant because everything's tracking. The you know, if you 546 00:29:55,000 --> 00:29:57,840 Speaker 1: follow the home builders and you follow the new home sales, 547 00:29:58,080 --> 00:30:00,240 Speaker 1: they're pretty much tracking. So let's let's talk a little 548 00:30:00,280 --> 00:30:04,040 Speaker 1: more about housing. My friend Jonathan Miller, who's a highly 549 00:30:04,080 --> 00:30:08,840 Speaker 1: regarded appraiser and data assembly on housing, has been talking 550 00:30:08,880 --> 00:30:11,800 Speaker 1: for a good couple of years about the problem with 551 00:30:11,880 --> 00:30:15,720 Speaker 1: no equity and low equity homeowners and it sort of 552 00:30:15,800 --> 00:30:19,560 Speaker 1: gums up the chain of purchases. In other words, Hey, 553 00:30:19,600 --> 00:30:21,840 Speaker 1: we're in a starter home. Up, we have a second 554 00:30:21,920 --> 00:30:24,280 Speaker 1: kid on the way. Let's sell this house, move up 555 00:30:24,280 --> 00:30:27,240 Speaker 1: to a four bedroom, the people selling that house move 556 00:30:27,320 --> 00:30:29,600 Speaker 1: up to a larger house, and those people move up 557 00:30:29,840 --> 00:30:31,920 Speaker 1: to the big mansions. But as long as the people 558 00:30:31,960 --> 00:30:35,120 Speaker 1: at the bottom starter home are are kind of stuck 559 00:30:35,120 --> 00:30:37,840 Speaker 1: there because they don't have enough equity, the whole system 560 00:30:37,920 --> 00:30:41,120 Speaker 1: is sort of compromised, and it means that there just 561 00:30:41,240 --> 00:30:45,400 Speaker 1: isn't enough supply out there. How does how does that sound? Yeah? Yeah, 562 00:30:45,440 --> 00:30:49,320 Speaker 1: well you know that that is a problem. And and 563 00:30:48,960 --> 00:30:52,720 Speaker 1: and housing historically always has been this kind of chain reaction. 564 00:30:52,760 --> 00:30:55,040 Speaker 1: One guy sells and he can buy in another sell 565 00:30:55,120 --> 00:30:57,200 Speaker 1: and buy and sell and buy, and so the situation 566 00:30:57,320 --> 00:31:00,480 Speaker 1: we're in today's is pretty unique. Um. One of the 567 00:31:00,520 --> 00:31:03,280 Speaker 1: things that's rarely mentioned is is that the reason there's 568 00:31:03,400 --> 00:31:07,520 Speaker 1: such low inventory, especially at the lower ends, is because 569 00:31:07,560 --> 00:31:10,840 Speaker 1: of all those investors buying millions and millions of by 570 00:31:10,920 --> 00:31:13,880 Speaker 1: the rent, by the fix and flip, by the Yeah, yeah, 571 00:31:13,920 --> 00:31:15,680 Speaker 1: the fix and flip doesn't hurt the market, but the 572 00:31:15,840 --> 00:31:17,880 Speaker 1: but the by the rent, by to rent, there's a 573 00:31:18,000 --> 00:31:20,440 Speaker 1: there's millions of homes that were bought to rent and 574 00:31:20,560 --> 00:31:22,840 Speaker 1: at a huge discount right the height of the crisis. 575 00:31:23,120 --> 00:31:25,680 Speaker 1: And and so those guys and and and I talked 576 00:31:25,720 --> 00:31:30,160 Speaker 1: to some of those guys in private equity or orstors combination. 577 00:31:30,640 --> 00:31:33,080 Speaker 1: You know, I know moms and pops that bought six 578 00:31:33,160 --> 00:31:38,240 Speaker 1: eight places. I know some larger investors that bought thousands 579 00:31:38,560 --> 00:31:41,200 Speaker 1: and and uh and for the most part, none of 580 00:31:41,280 --> 00:31:45,800 Speaker 1: them are selling really Yeah, so they know why is that? Well, okay, 581 00:31:46,080 --> 00:31:48,920 Speaker 1: if they sell, they have to play capital gains and 582 00:31:48,960 --> 00:31:50,960 Speaker 1: then and there's one short way to make sure you 583 00:31:51,040 --> 00:31:54,160 Speaker 1: never pay capital gains taxes. Don't have a capital gain. Yeah, 584 00:31:54,440 --> 00:31:58,000 Speaker 1: So that's always to me, not a great reason not 585 00:31:58,080 --> 00:32:00,560 Speaker 1: to sell. Yeah, but but where else they're gonna put 586 00:32:00,600 --> 00:32:01,720 Speaker 1: them up? But then they have to move it to 587 00:32:01,760 --> 00:32:04,200 Speaker 1: somewhere else, right, and and you know, what are you 588 00:32:04,200 --> 00:32:07,360 Speaker 1: gonna do? And and those guys rents have gone up substantially. 589 00:32:07,800 --> 00:32:11,000 Speaker 1: They were buying these things with cap rates of when 590 00:32:11,040 --> 00:32:13,200 Speaker 1: they bought them, and the and the rents have gone 591 00:32:13,280 --> 00:32:16,400 Speaker 1: up dramatically, so on their original money, they're just they're 592 00:32:16,440 --> 00:32:18,520 Speaker 1: just cranking it. If they sell it, even if they 593 00:32:18,520 --> 00:32:21,440 Speaker 1: can avoid paying capital gains. If they sell it, avoid 594 00:32:21,720 --> 00:32:23,840 Speaker 1: capital gains, where do they put their money and get 595 00:32:23,880 --> 00:32:28,680 Speaker 1: that same return? You get one five one on the tenure. Yeah, yeah, 596 00:32:28,720 --> 00:32:32,880 Speaker 1: that's not negative yet, it's a positive. So those you know, 597 00:32:33,000 --> 00:32:35,840 Speaker 1: I I know several people personally that own you know, 598 00:32:35,880 --> 00:32:38,520 Speaker 1: maybe three or eight. They'd rather just get the income 599 00:32:38,520 --> 00:32:40,640 Speaker 1: and they're never going to sell them. We've been speaking 600 00:32:40,640 --> 00:32:43,840 Speaker 1: with Bill McBride. He is the founder and chief blogger 601 00:32:43,920 --> 00:32:48,120 Speaker 1: at Calculated Risk. Be sure and check out the site 602 00:32:48,160 --> 00:32:52,600 Speaker 1: Calculated Risk for just an incredible slew of economic data, 603 00:32:52,720 --> 00:32:57,000 Speaker 1: charts and analysis. If you enjoy this conversation be shown 604 00:32:57,120 --> 00:33:00,280 Speaker 1: check out our podcast extras, where we keep the digital 605 00:33:00,320 --> 00:33:05,160 Speaker 1: tape rolling and continue to discuss all things economic and digital. 606 00:33:05,800 --> 00:33:09,160 Speaker 1: Check out my daily column on Bloomberg View dot com 607 00:33:09,280 --> 00:33:12,800 Speaker 1: or follow me on Twitter at rid Halts. We love 608 00:33:12,840 --> 00:33:17,280 Speaker 1: your emails and comments. Please write to us at m 609 00:33:17,320 --> 00:33:22,480 Speaker 1: IB podcast at Bloomberg dot net. I'm Barry rid Halts. 610 00:33:22,520 --> 00:33:27,400 Speaker 1: You're listening to Masters in Business on Bloomberg Radio. Welcome 611 00:33:27,440 --> 00:33:30,640 Speaker 1: to the podcast. This is Barry ridhalts Bill. Thank you 612 00:33:30,680 --> 00:33:34,240 Speaker 1: so much for doing this. You know, you and my pleasure. 613 00:33:34,360 --> 00:33:38,600 Speaker 1: You and I have been ranting each other, no exaggeration. 614 00:33:39,120 --> 00:33:44,160 Speaker 1: It's got to be ten twelve years. I think we 615 00:33:44,240 --> 00:33:46,280 Speaker 1: had dinner this week. I think that's the first time 616 00:33:46,280 --> 00:33:50,000 Speaker 1: you met in person. Is that right? So I have 617 00:33:50,280 --> 00:33:55,200 Speaker 1: tons of of of stories and anecdotes. There's so many 618 00:33:55,280 --> 00:33:58,200 Speaker 1: questions to get through. And before I get to my 619 00:33:58,520 --> 00:34:02,000 Speaker 1: standard questions, there's there's just there's just so much stuff 620 00:34:02,000 --> 00:34:05,600 Speaker 1: I have to do. Um. By the way, before we 621 00:34:05,640 --> 00:34:08,080 Speaker 1: get to those questions, how are you enjoying your your 622 00:34:08,360 --> 00:34:10,480 Speaker 1: week in New York. I'm having a great time. The 623 00:34:10,760 --> 00:34:13,399 Speaker 1: weather couldn't be nicer. Yeah, yeah, thank you so much. 624 00:34:13,480 --> 00:34:16,439 Speaker 1: You you it was miserable, ninety and humid last week. 625 00:34:16,520 --> 00:34:18,759 Speaker 1: It's been it's been perfect today. I went for a 626 00:34:18,800 --> 00:34:21,040 Speaker 1: walk in the Central Park this morning. But it's been 627 00:34:21,120 --> 00:34:25,200 Speaker 1: it's been delightful. So so you're now spending to three 628 00:34:25,560 --> 00:34:29,920 Speaker 1: four hours a day blogging in the midst of the crisis, 629 00:34:30,200 --> 00:34:32,919 Speaker 1: oh eight oh nine, how much time will you devot 630 00:34:33,000 --> 00:34:35,880 Speaker 1: into the sun? I was probably spending maybe eight hours 631 00:34:35,880 --> 00:34:38,320 Speaker 1: a day full, a full day's work. But but I 632 00:34:38,360 --> 00:34:40,880 Speaker 1: was up, you know at five in the morning, uh, 633 00:34:40,920 --> 00:34:43,279 Speaker 1: and and doing work. And I was, you know, right 634 00:34:43,320 --> 00:34:45,600 Speaker 1: before I went to bed, I was doing work and 635 00:34:45,800 --> 00:34:48,640 Speaker 1: not it's not nine to five, it's it's all day. 636 00:34:48,680 --> 00:34:52,040 Speaker 1: It's digital sixteen seventeen hours a day. I did sleep 637 00:34:52,040 --> 00:34:53,920 Speaker 1: a little, and every once in a while they have 638 00:34:53,920 --> 00:34:55,160 Speaker 1: to set my alarm clock for the middle of the 639 00:34:55,200 --> 00:34:58,200 Speaker 1: night because I knew something crazy was coming when oh really, 640 00:34:58,239 --> 00:35:01,120 Speaker 1: so you would wake up to see, especially when stuff 641 00:35:01,120 --> 00:35:03,600 Speaker 1: was coming from Europe. You know, I'd be going all great, 642 00:35:04,000 --> 00:35:07,960 Speaker 1: I see my attitude as always, well it'll be there, Yes, 643 00:35:08,239 --> 00:35:10,080 Speaker 1: it'll be there in the morning. That's my attitude. Now 644 00:35:10,280 --> 00:35:13,320 Speaker 1: when when did you realize that the site was really 645 00:35:13,360 --> 00:35:17,000 Speaker 1: catching on? Uh? You know it kind of it kind 646 00:35:17,040 --> 00:35:21,200 Speaker 1: of just build. It's a boiled frog. Yeah, it happened 647 00:35:21,239 --> 00:35:23,040 Speaker 1: over time. You know. It was interesting because at first, 648 00:35:23,080 --> 00:35:25,279 Speaker 1: I'd say the first month because you see the traffic data. 649 00:35:25,520 --> 00:35:27,560 Speaker 1: You know, I was just sending it to friends and relatives. 650 00:35:27,840 --> 00:35:29,960 Speaker 1: All those posts now have lots of his but that's 651 00:35:29,960 --> 00:35:33,320 Speaker 1: because people have gone back in time, you know, maybe 652 00:35:33,320 --> 00:35:37,200 Speaker 1: in February two thousand five, Dr David, I'll tag of 653 00:35:37,760 --> 00:35:41,200 Speaker 1: Cleveland FED or Atlanta FED. Now, I guess he stumbled 654 00:35:41,239 --> 00:35:44,840 Speaker 1: on my blog somehow and he mentioned something that I 655 00:35:44,880 --> 00:35:47,880 Speaker 1: had written, and all of a sudden, my traffic was, 656 00:35:48,000 --> 00:35:50,360 Speaker 1: you know, a hundred readers a day out of the 657 00:35:50,360 --> 00:35:54,080 Speaker 1: blue readers a day, and and uh, and I went wow, 658 00:35:54,080 --> 00:35:57,400 Speaker 1: what happened there? And then something interesting happened is one 659 00:35:57,440 --> 00:36:00,000 Speaker 1: of those readers was one of the three PhD economists 660 00:36:00,320 --> 00:36:03,400 Speaker 1: at Angry Bear, and he called me up and say, hey, 661 00:36:03,680 --> 00:36:06,399 Speaker 1: could you write a weekly column about housing? Because that's 662 00:36:06,400 --> 00:36:08,399 Speaker 1: because I was completely focused on housing at the time, 663 00:36:08,840 --> 00:36:10,920 Speaker 1: and so I wrote a good reason. Yeah, I wrote that, 664 00:36:11,000 --> 00:36:13,600 Speaker 1: and within several months I was up to two thousand 665 00:36:13,640 --> 00:36:17,400 Speaker 1: readers a day. And what was the peak traffic in 666 00:36:17,920 --> 00:36:22,479 Speaker 1: oh eight oh nine? Yeah, probably averaged throughout oh eight 667 00:36:22,600 --> 00:36:26,239 Speaker 1: and in oh nine probably add twenty thousand readers a day. 668 00:36:26,520 --> 00:36:30,720 Speaker 1: What does that work out to be on a monthly basis? Uh? 669 00:36:31,040 --> 00:36:35,560 Speaker 1: I was probably four million, three four millions. It went crazy. 670 00:36:35,680 --> 00:36:39,080 Speaker 1: It was crazy. It was crazy. And then I'm probably 671 00:36:39,120 --> 00:36:43,120 Speaker 1: less cut and half after that. Yeah, I'm probably now right, 672 00:36:43,360 --> 00:36:46,480 Speaker 1: you know, maybe forty readers a day. But these are 673 00:36:46,480 --> 00:36:50,359 Speaker 1: forty important influential readers. Yeah, well they're you know, they're 674 00:36:50,360 --> 00:36:53,239 Speaker 1: obviously people that are very interested in economicus. And we 675 00:36:53,320 --> 00:36:56,200 Speaker 1: talked a little bit during the broadcast portion about comments. 676 00:36:56,719 --> 00:37:01,200 Speaker 1: How frustrating is it that comments was once so crucial, 677 00:37:01,400 --> 00:37:05,719 Speaker 1: so seminal, and now they're just a wreck. Well, you know, 678 00:37:05,880 --> 00:37:08,920 Speaker 1: in general, I don't I mean our our comments since 679 00:37:08,960 --> 00:37:12,280 Speaker 1: you have to register. It's they're they're okay, but they're 680 00:37:12,320 --> 00:37:15,839 Speaker 1: they're more clicky, and and there their long term people 681 00:37:15,840 --> 00:37:19,800 Speaker 1: who just talk about off topic subjects with a queue, 682 00:37:19,800 --> 00:37:23,320 Speaker 1: not not web click. Yes, yes, like like it's groups 683 00:37:23,320 --> 00:37:26,719 Speaker 1: of people. Yeah, they they have their topics they want 684 00:37:26,760 --> 00:37:30,200 Speaker 1: to talk about. It's unrelated. It's really it's completely different 685 00:37:30,200 --> 00:37:32,440 Speaker 1: when when in two thousand five, two thousand and six, 686 00:37:32,520 --> 00:37:34,880 Speaker 1: when I would post something, the topics were on topic. 687 00:37:35,000 --> 00:37:38,359 Speaker 1: I mean the comments were on topic, uh and insightful. Yeah, 688 00:37:38,360 --> 00:37:39,799 Speaker 1: and that's why I met a lot of great people, 689 00:37:39,840 --> 00:37:42,880 Speaker 1: including my code blogger you know, to me, I was 690 00:37:42,920 --> 00:37:45,320 Speaker 1: talking about this a little bit earlier. Is I remember 691 00:37:45,400 --> 00:37:48,040 Speaker 1: using Yahoo Finance when it first came out. That's you'd 692 00:37:48,040 --> 00:37:50,400 Speaker 1: comment on a company and the comments are great. It 693 00:37:50,400 --> 00:37:52,560 Speaker 1: didn't take long since they were all public for that 694 00:37:52,640 --> 00:37:55,400 Speaker 1: just to go completely downhill and be completely useless. In 695 00:37:55,440 --> 00:37:59,680 Speaker 1: the nineties, I very vividly so I began as a 696 00:37:59,680 --> 00:38:02,719 Speaker 1: trade in the in the mid nineties, and I very 697 00:38:02,840 --> 00:38:07,400 Speaker 1: vividly remember stumbling into Yahoo comments and a family member 698 00:38:07,440 --> 00:38:10,640 Speaker 1: had this huge position in I Omega had split two 699 00:38:10,719 --> 00:38:13,520 Speaker 1: one two for one. What started out as a ten 700 00:38:13,600 --> 00:38:17,040 Speaker 1: thousand dollar investment was like a three million dollar holding. 701 00:38:17,400 --> 00:38:22,839 Speaker 1: And I remember following the Omega Yahoo message boards with 702 00:38:22,960 --> 00:38:25,560 Speaker 1: people driving I think the factory was in Utah or 703 00:38:25,600 --> 00:38:29,160 Speaker 1: some crazy thing, driving by the factory on a Sunday 704 00:38:29,320 --> 00:38:34,919 Speaker 1: and all Wall Street is underestimating the revenue and profit numbers. Hey, 705 00:38:34,960 --> 00:38:38,840 Speaker 1: the factory parking lot is filled with cars on a 706 00:38:38,920 --> 00:38:41,960 Speaker 1: Sunday night. These guys are working double and triple shifts, 707 00:38:42,000 --> 00:38:45,120 Speaker 1: like it was that sort of serious investment was It 708 00:38:45,200 --> 00:38:47,799 Speaker 1: was awesome. You get that, You get that kind of 709 00:38:47,840 --> 00:38:52,480 Speaker 1: local color. Somebody knew something about the company, not insider information, 710 00:38:52,560 --> 00:38:57,160 Speaker 1: driving by just a parking lot. That's public, man, It's 711 00:38:57,200 --> 00:39:00,239 Speaker 1: it's amazing, so and and and you the only you 712 00:39:00,239 --> 00:39:02,000 Speaker 1: could get a little bit of that on tweeter. Now 713 00:39:03,280 --> 00:39:05,319 Speaker 1: somebody might take a picture of the parking lot. Of course, 714 00:39:05,360 --> 00:39:06,719 Speaker 1: then you got and you don't really know if it's 715 00:39:06,760 --> 00:39:09,080 Speaker 1: real or not that that's become and there's been a 716 00:39:09,080 --> 00:39:11,960 Speaker 1: lot of scams and hacks and things. You really have 717 00:39:12,000 --> 00:39:14,480 Speaker 1: to be careful with with what you see. You know, 718 00:39:15,800 --> 00:39:19,719 Speaker 1: I've talked about this very very little. I wrote Bailout 719 00:39:19,800 --> 00:39:24,680 Speaker 1: Nation with my commenters. I would post up three word 720 00:39:24,680 --> 00:39:27,080 Speaker 1: of forenger word thing in the evening that I had 721 00:39:27,080 --> 00:39:29,400 Speaker 1: written during the day. What do you think about this? 722 00:39:29,520 --> 00:39:31,640 Speaker 1: Tell me your thoughts, and people would say, have you 723 00:39:31,680 --> 00:39:33,960 Speaker 1: seen this article in the Christian Science Monitor off? You know, 724 00:39:34,080 --> 00:39:36,359 Speaker 1: because obviously the front page of the Wall Street Journal 725 00:39:36,360 --> 00:39:39,319 Speaker 1: in the New York Times everybody sees. So you have 726 00:39:39,400 --> 00:39:43,560 Speaker 1: this huge research team and people making suggestions and comments. 727 00:39:44,120 --> 00:39:50,480 Speaker 1: The golden age of blog comments was unlike anything. You know. 728 00:39:50,480 --> 00:39:53,320 Speaker 1: It's funny because one of my commenters wrote a fiction 729 00:39:53,360 --> 00:39:56,880 Speaker 1: book partially in the comments, called American Apocalypse. He's a lawyer. 730 00:39:57,080 --> 00:40:01,719 Speaker 1: Unfortunately has passed away now, but he It became a 731 00:40:01,760 --> 00:40:05,319 Speaker 1: pretty good seller on Amazon, and he wrote it in 732 00:40:05,360 --> 00:40:07,560 Speaker 1: the comments and people with It was a fiction thing about, 733 00:40:07,600 --> 00:40:10,080 Speaker 1: you know, if the financial crisis had really gotten dad, 734 00:40:10,480 --> 00:40:14,480 Speaker 1: I mean total second great depression or worse. And but 735 00:40:14,480 --> 00:40:16,440 Speaker 1: but you know, it's just kind of like you and 736 00:40:16,480 --> 00:40:18,160 Speaker 1: bell on Nation, except for he started it in the 737 00:40:18,200 --> 00:40:20,040 Speaker 1: comments and it was fun. It was kind of fun. 738 00:40:21,040 --> 00:40:24,719 Speaker 1: Have you ever gotten invites to speak or or take 739 00:40:24,760 --> 00:40:30,280 Speaker 1: a meeting with anybody from Treasury, Department, Federal Reserve, House, 740 00:40:30,400 --> 00:40:34,840 Speaker 1: Joint Economics Committee, anything like? Nothing? Well, the Treasury invited 741 00:40:34,880 --> 00:40:38,800 Speaker 1: me back once. Um, but that that was it. Uh. 742 00:40:38,960 --> 00:40:42,160 Speaker 1: When you say he invited you back, they they. If 743 00:40:42,200 --> 00:40:45,000 Speaker 1: I came, I got to to, you know, meet some 744 00:40:45,160 --> 00:40:48,440 Speaker 1: senior people. But but I was in California, so it 745 00:40:48,480 --> 00:40:51,840 Speaker 1: wasn't very union for me. I got the Tim Geithner invite, 746 00:40:51,880 --> 00:40:55,080 Speaker 1: which I think was the public relations Yes, did you 747 00:40:55,120 --> 00:40:57,319 Speaker 1: go to that? See, that's the one I was talking about. 748 00:40:57,400 --> 00:41:01,279 Speaker 1: And did you go to that? No, I was in California. 749 00:41:01,320 --> 00:41:03,239 Speaker 1: It's too far. It was in New York. It was 750 00:41:03,280 --> 00:41:05,560 Speaker 1: too far because it just smelled like one of those things. 751 00:41:05,600 --> 00:41:07,960 Speaker 1: Come on in, he'll come in, shake some hands to 752 00:41:08,040 --> 00:41:10,479 Speaker 1: a photo op. And why did I travel three hours 753 00:41:10,520 --> 00:41:14,319 Speaker 1: each way for this? It was? I politely responded and said, hey, 754 00:41:14,400 --> 00:41:16,359 Speaker 1: let me know the next time Tim is in New York. 755 00:41:16,400 --> 00:41:18,560 Speaker 1: I'm happy to meet with him, but I'm not interested 756 00:41:18,560 --> 00:41:21,120 Speaker 1: in a photo op. And that's that was the sort 757 00:41:21,160 --> 00:41:23,840 Speaker 1: of outreach trip. Oh, these bloggers are causing us trouble. 758 00:41:23,920 --> 00:41:26,160 Speaker 1: Let's let's did you ever get a sense that you 759 00:41:26,200 --> 00:41:30,600 Speaker 1: were causing trouble too, elected officials? Not at all. I 760 00:41:30,680 --> 00:41:34,400 Speaker 1: never felt that at all. I um no, you know, 761 00:41:34,560 --> 00:41:36,480 Speaker 1: there there was a time I think there was a 762 00:41:36,480 --> 00:41:39,799 Speaker 1: lot of resentment from the media about blogging. Let's talk 763 00:41:39,800 --> 00:41:42,000 Speaker 1: about that. I used to do this thing, and I 764 00:41:42,040 --> 00:41:45,520 Speaker 1: know Tanted did something similar called read it here. First 765 00:41:45,840 --> 00:41:49,480 Speaker 1: in the beginning when so I launched the Big Picture 766 00:41:49,520 --> 00:41:52,160 Speaker 1: and oh three, but before that it was a Yahoo 767 00:41:52,239 --> 00:41:56,720 Speaker 1: Geo City site. And after No. Eleven I had written 768 00:41:56,760 --> 00:41:59,120 Speaker 1: a piece that kind of had gone viral. So it's like, oh, 769 00:41:59,200 --> 00:42:02,160 Speaker 1: this internet thing going to be big one day. And 770 00:42:02,239 --> 00:42:06,080 Speaker 1: so I would notice the amazing coincidence. You'd write about 771 00:42:06,120 --> 00:42:08,759 Speaker 1: something and then a day or a week later it 772 00:42:08,760 --> 00:42:12,040 Speaker 1: would show up in Wall Street Journal, New York Times, Barons, 773 00:42:12,080 --> 00:42:16,520 Speaker 1: Business everywhere, the whole media. And my initial well, no 774 00:42:16,560 --> 00:42:20,120 Speaker 1: one would just steal this. I must have picked something 775 00:42:20,239 --> 00:42:24,120 Speaker 1: up and other people from wherever whatever motivated me to 776 00:42:24,160 --> 00:42:27,440 Speaker 1: write this, so they must have been motivated by the 777 00:42:27,440 --> 00:42:28,680 Speaker 1: same thing. I don't want to say it was in 778 00:42:28,719 --> 00:42:31,920 Speaker 1: the ether. But if I'm looking at an economic news release, 779 00:42:31,960 --> 00:42:34,560 Speaker 1: and Bill is looking at an economic news release, and 780 00:42:34,600 --> 00:42:37,440 Speaker 1: a reporter at x y Z paper is looking at that, 781 00:42:37,840 --> 00:42:41,000 Speaker 1: we're all looking at the same thing. And I assumed 782 00:42:41,000 --> 00:42:44,200 Speaker 1: it was a coincidence. And that changed. In two thousand 783 00:42:44,200 --> 00:42:50,440 Speaker 1: and four, I wrote a long form piece called Radio's 784 00:42:50,640 --> 00:42:55,160 Speaker 1: Wounded Business Model that basically trashed Clear Channel Communications and 785 00:42:55,480 --> 00:43:01,560 Speaker 1: trashed Infinity Broadcasting. It was really just rant and a 786 00:43:02,440 --> 00:43:06,080 Speaker 1: maybe it was. Three weeks later Barons has a cover 787 00:43:06,239 --> 00:43:10,560 Speaker 1: story and I'm a music buff and I hate program radio. 788 00:43:11,000 --> 00:43:15,400 Speaker 1: This wasn't motivated by anything out there. This was just 789 00:43:15,520 --> 00:43:18,440 Speaker 1: me going on a jag. And then Barons has a 790 00:43:18,440 --> 00:43:22,120 Speaker 1: cover story called Losing the Signal, and it was practically 791 00:43:22,160 --> 00:43:24,759 Speaker 1: a point by point thing. And that was a moment 792 00:43:24,760 --> 00:43:27,320 Speaker 1: where it dawned on me that hey, it's not in 793 00:43:27,360 --> 00:43:31,760 Speaker 1: the ether. These people are ripping you off. What Tanta 794 00:43:31,840 --> 00:43:35,239 Speaker 1: did something, well, tell us what what she did with 795 00:43:35,320 --> 00:43:38,080 Speaker 1: a similar bit of a thievery well, you know. But 796 00:43:38,280 --> 00:43:41,360 Speaker 1: first I was working with a lot of reporters on 797 00:43:41,360 --> 00:43:44,799 Speaker 1: on their stories, and you were anonymous back then. Yeah, 798 00:43:44,840 --> 00:43:48,240 Speaker 1: I would have people would call me up um and 799 00:43:48,239 --> 00:43:52,200 Speaker 1: and and uh we would chat about a story, possible angles, 800 00:43:53,200 --> 00:43:56,960 Speaker 1: ways to write it, and and every time they would go, I, 801 00:43:57,280 --> 00:44:00,400 Speaker 1: my editor will not let me mention that you're writing 802 00:44:00,400 --> 00:44:03,080 Speaker 1: a blog calculator risk. Can can I mention that you 803 00:44:03,160 --> 00:44:05,640 Speaker 1: used to be the executive this company? Use your real name? 804 00:44:05,680 --> 00:44:08,000 Speaker 1: I said, no, you know, if you can't, I'll help 805 00:44:08,040 --> 00:44:10,360 Speaker 1: you the on stories all you want that's there and 806 00:44:10,480 --> 00:44:13,960 Speaker 1: that good will over time paid off. But the you know, 807 00:44:14,040 --> 00:44:16,279 Speaker 1: I said no, I I just want to stay anonymous. 808 00:44:17,000 --> 00:44:19,239 Speaker 1: I didn't know why at the time, but it was 809 00:44:19,280 --> 00:44:23,360 Speaker 1: just kind of fun for me. And and you were retired, 810 00:44:23,400 --> 00:44:25,719 Speaker 1: you weren't looking to Yeah, I was. I wasn't. I 811 00:44:25,760 --> 00:44:27,279 Speaker 1: wasn't trying to make any money. I wasn't trying to 812 00:44:27,320 --> 00:44:30,680 Speaker 1: start a war. Uh Tanta. When when she came on, 813 00:44:30,920 --> 00:44:34,279 Speaker 1: she used to call me up. Yeah, she go, Bill, 814 00:44:34,280 --> 00:44:36,800 Speaker 1: they ripped off your story or they ripped off my story. 815 00:44:36,880 --> 00:44:39,399 Speaker 1: And and so then she wrote a piece about how 816 00:44:39,800 --> 00:44:42,880 Speaker 1: you know, if if if you want to use our 817 00:44:42,920 --> 00:44:46,160 Speaker 1: information point you really should mention that you where you 818 00:44:46,239 --> 00:44:49,640 Speaker 1: got it from. That's just kind of standard practice in journalism. 819 00:44:49,719 --> 00:44:54,040 Speaker 1: And uh yeah, and and and several journalism professors have 820 00:44:54,120 --> 00:44:57,720 Speaker 1: told me they use her piece two and they teach 821 00:44:57,760 --> 00:45:02,560 Speaker 1: it in their classes, colleges, and and and it was 822 00:45:02,640 --> 00:45:05,680 Speaker 1: immediately after that that we started getting mentioned everywhere. And 823 00:45:05,760 --> 00:45:08,400 Speaker 1: you know a lot of the reporters I know wanted 824 00:45:08,480 --> 00:45:12,400 Speaker 1: to mention us much sooner. So it was editorial and publishing, 825 00:45:12,440 --> 00:45:15,880 Speaker 1: not the actual right. Yes, the writer. Listen, writers, I 826 00:45:15,920 --> 00:45:18,399 Speaker 1: write a daily column. It's drummed into your head from 827 00:45:18,440 --> 00:45:23,200 Speaker 1: day one. Always source, always link, always quote, always footnote, 828 00:45:23,680 --> 00:45:27,160 Speaker 1: don't just take. And my nightmare is reading something and 829 00:45:27,280 --> 00:45:31,560 Speaker 1: kind of subconsciously ferreting it away and then it comes 830 00:45:31,560 --> 00:45:33,680 Speaker 1: out and it's like, oh, I I ripped someone off 831 00:45:33,680 --> 00:45:36,520 Speaker 1: by accident. That's my nightmare scenario. Yeah, you know you 832 00:45:37,040 --> 00:45:39,120 Speaker 1: and and and I think that's always hard for a writer. 833 00:45:39,239 --> 00:45:42,880 Speaker 1: I I I try to be very very careful and 834 00:45:43,400 --> 00:45:46,480 Speaker 1: linked to everything and and uh so what what I 835 00:45:46,520 --> 00:45:50,640 Speaker 1: started doing after the Baron's piece that to me was clearly, oh, 836 00:45:50,719 --> 00:45:55,400 Speaker 1: this isn't even nuance, this is just blatant. So I 837 00:45:55,440 --> 00:45:57,960 Speaker 1: started a series of reading here first columns, and I 838 00:45:57,960 --> 00:46:01,280 Speaker 1: would do side by side the two column I'd highlight 839 00:46:01,320 --> 00:46:05,200 Speaker 1: stuff I'd put on the blog, and especially with the 840 00:46:05,200 --> 00:46:10,160 Speaker 1: the outlets that included the author and editors. I never 841 00:46:10,200 --> 00:46:12,080 Speaker 1: had that from Bloomberg, and I'm not just saying that 842 00:46:12,080 --> 00:46:15,200 Speaker 1: because I'm here, but I've had it from because their 843 00:46:15,280 --> 00:46:19,640 Speaker 1: sources they have a really crazy strict sourcing mechanism. But 844 00:46:19,680 --> 00:46:23,040 Speaker 1: a lot of other places, I would take the two pieces, 845 00:46:23,239 --> 00:46:25,799 Speaker 1: say what a coincidence. I wrote this on Monday, you 846 00:46:25,840 --> 00:46:28,320 Speaker 1: published this on Tuesday. I would send it to the reporter. 847 00:46:28,360 --> 00:46:30,920 Speaker 1: I would send it to the editor, and I would 848 00:46:31,320 --> 00:46:34,400 Speaker 1: sort of politely on the blogs say read it here first, 849 00:46:35,000 --> 00:46:38,279 Speaker 1: And eventually I think they became embarrassed. So like oh 850 00:46:38,280 --> 00:46:41,600 Speaker 1: four or five, oh six, once you got into oh 851 00:46:41,600 --> 00:46:44,319 Speaker 1: seven and oh eight, and I was you know, I 852 00:46:44,360 --> 00:46:47,800 Speaker 1: had an official job title where I was a media 853 00:46:48,040 --> 00:46:51,040 Speaker 1: a market strategist and a media spokesperson, So it was 854 00:46:51,120 --> 00:46:53,600 Speaker 1: easy for me to say, hey, you don't have to 855 00:46:53,680 --> 00:46:58,040 Speaker 1: quote the blog, but at least credit the source. You 856 00:46:58,040 --> 00:47:00,080 Speaker 1: don't even have to link to it, but you know 857 00:47:00,160 --> 00:47:03,120 Speaker 1: you're stealing my work products. Well, you know, they would 858 00:47:03,760 --> 00:47:07,080 Speaker 1: the media would mention people like professor Jim Hamilton and 859 00:47:07,080 --> 00:47:11,080 Speaker 1: San Diego or Mark Thomas um but they'd always mentioned that, oh, 860 00:47:11,120 --> 00:47:13,880 Speaker 1: Mark Thomas a professor at University of Oregon. There was 861 00:47:13,920 --> 00:47:16,239 Speaker 1: an official tie. Yeah, not that he's writing a site 862 00:47:16,239 --> 00:47:19,319 Speaker 1: called the Economist View, which had the information you know 863 00:47:19,360 --> 00:47:21,759 Speaker 1: and say, so you know that that's what they were 864 00:47:21,800 --> 00:47:25,480 Speaker 1: comfortable doing, but not the referencing the blogs. It took 865 00:47:25,680 --> 00:47:28,960 Speaker 1: a different but they shifted and they sure, well what 866 00:47:29,120 --> 00:47:31,400 Speaker 1: first they rolled out their own blogs? Yeah, and and 867 00:47:31,400 --> 00:47:36,480 Speaker 1: then they realized that that it's all complimentary anyway. In fact, uh, 868 00:47:36,600 --> 00:47:39,680 Speaker 1: we would drive traffic for them. We mentioned that, oh 869 00:47:39,719 --> 00:47:41,600 Speaker 1: hey wait they you know, this guy had a good 870 00:47:41,600 --> 00:47:43,560 Speaker 1: thing about this, and and people would go read that 871 00:47:43,640 --> 00:47:46,560 Speaker 1: traffic And it got to the point where, uh, journalists 872 00:47:46,560 --> 00:47:49,279 Speaker 1: would send me their articles and say, hey, if you 873 00:47:49,320 --> 00:47:51,160 Speaker 1: like this, could you could you mention it or linked 874 00:47:51,160 --> 00:47:57,080 Speaker 1: to it or or if yeah, and and and uh 875 00:47:57,480 --> 00:47:59,719 Speaker 1: it really helped them. They would they when did that 876 00:48:00,040 --> 00:48:02,120 Speaker 1: lip take? When did it go from O blobs we 877 00:48:02,160 --> 00:48:04,480 Speaker 1: could steal with impunity and no, it had to be 878 00:48:04,480 --> 00:48:07,160 Speaker 1: in two thousand seven. Two thousand seven, that's when you 879 00:48:07,200 --> 00:48:10,759 Speaker 1: first started noticing people asking yeah, and and and all 880 00:48:10,760 --> 00:48:12,839 Speaker 1: of a sudden we were and it really boosted our 881 00:48:12,840 --> 00:48:15,719 Speaker 1: traffic to did did you ever get day loosed with 882 00:48:15,840 --> 00:48:19,200 Speaker 1: pr pitches? Hey would you like to meet the executive sales? 883 00:48:19,360 --> 00:48:22,640 Speaker 1: Well you get that every day, you do, Yes, every 884 00:48:22,719 --> 00:48:29,320 Speaker 1: day I relentlessly, relentlessly black Matt Black um list those 885 00:48:29,520 --> 00:48:33,840 Speaker 1: the people that just sends ridiculous. It's one thing that 886 00:48:33,880 --> 00:48:37,520 Speaker 1: it's unsolicited, but I don't really care about the sixteen 887 00:48:37,600 --> 00:48:40,840 Speaker 1: year old girls new pop song that's not relevant to 888 00:48:40,840 --> 00:48:43,480 Speaker 1: what we're reading. Yeah, well, you know I I I 889 00:48:43,520 --> 00:48:45,600 Speaker 1: think I saw the other day there's more PR people 890 00:48:45,640 --> 00:48:49,040 Speaker 1: now than there are journalists in America two to one, 891 00:48:49,120 --> 00:48:54,040 Speaker 1: or something that explains. That explains, that explains a whole lot. 892 00:48:54,680 --> 00:48:57,400 Speaker 1: Oh my god, that's awful. That that is a horrible, 893 00:48:57,440 --> 00:49:01,880 Speaker 1: horrible thought. Um On on the terminal, you have this 894 00:49:01,920 --> 00:49:04,920 Speaker 1: option on the bloomber terminal, you have this option. So 895 00:49:05,080 --> 00:49:08,160 Speaker 1: every now and then a reasonable PR pitch comes in 896 00:49:08,280 --> 00:49:12,520 Speaker 1: or or read will say so. I had Jeff Maggian Calda, 897 00:49:12,600 --> 00:49:15,840 Speaker 1: who is the founder and former CEO of Financial Engines, 898 00:49:16,360 --> 00:49:20,680 Speaker 1: which they work with Nobel Laureate Bill Sharp, and they 899 00:49:20,719 --> 00:49:24,200 Speaker 1: were really one of the first entities out there to 900 00:49:24,360 --> 00:49:27,719 Speaker 1: do what people are calling robo advising today. But it 901 00:49:27,800 --> 00:49:32,480 Speaker 1: was Bill Sharp and an entire four way to manage 902 00:49:32,520 --> 00:49:36,560 Speaker 1: for one case through a series of intelligent algorithms, and 903 00:49:36,600 --> 00:49:39,880 Speaker 1: they run like a hundred plus billion dollars. So someone 904 00:49:39,920 --> 00:49:42,520 Speaker 1: who worked for the company, sends an email, I love 905 00:49:42,600 --> 00:49:47,319 Speaker 1: the podcast. Are you familiar with Magine, Calda and Financial Engines? No? 906 00:49:47,400 --> 00:49:49,640 Speaker 1: I never even heard of them. Their public company this 907 00:49:49,719 --> 00:49:51,719 Speaker 1: and that. So I look them up. I'm like, how 908 00:49:51,760 --> 00:49:54,080 Speaker 1: have I never heard about these guys? They are all 909 00:49:54,239 --> 00:49:59,040 Speaker 1: rock stars. So that sort of pitch from somebody, that's 910 00:49:58,400 --> 00:50:01,960 Speaker 1: what It's a relevant pitch. Chin It's right and that 911 00:50:02,160 --> 00:50:06,080 Speaker 1: that wasn't even a PR person. I think it was. Um, 912 00:50:06,120 --> 00:50:09,560 Speaker 1: it was a quarry doctor at Boing Boing said, uh, 913 00:50:09,600 --> 00:50:13,320 Speaker 1: he published a whole list of so all these PR 914 00:50:13,400 --> 00:50:17,560 Speaker 1: shops email you and your black blacklist the PR shop. 915 00:50:17,880 --> 00:50:20,840 Speaker 1: So now you're getting these pitches from Gmail. So he 916 00:50:20,880 --> 00:50:22,759 Speaker 1: went out and published, I think was him. I hope 917 00:50:22,760 --> 00:50:25,440 Speaker 1: I'm not. He's getting the wrong person. A list of 918 00:50:25,520 --> 00:50:28,600 Speaker 1: everybody on this list is a PR wanker who is 919 00:50:29,560 --> 00:50:32,920 Speaker 1: using Gmail. They're multiplying so fast you can never So 920 00:50:33,320 --> 00:50:35,120 Speaker 1: here's a list. Add them to your black list and 921 00:50:35,160 --> 00:50:37,520 Speaker 1: you won't ever see anything from that. And I just 922 00:50:37,600 --> 00:50:40,840 Speaker 1: read that Apple and Google are now doing something similar 923 00:50:40,920 --> 00:50:46,080 Speaker 1: on the phone side. Um, it's amazing. How how this 924 00:50:46,200 --> 00:50:50,560 Speaker 1: problem so far, I've digressed so far. Let me jump 925 00:50:50,680 --> 00:50:53,600 Speaker 1: back to some of the questions that we just didn't 926 00:50:53,600 --> 00:50:57,160 Speaker 1: get a question, a chance to discuss. You mentioned your 927 00:50:57,360 --> 00:51:03,160 Speaker 1: you're we're publishing anonymously. What made you decide to come 928 00:51:03,160 --> 00:51:06,800 Speaker 1: out from behind the cloak of anonymity. Well, first, I 929 00:51:07,120 --> 00:51:09,960 Speaker 1: started that way just because I thought that's how you 930 00:51:10,000 --> 00:51:12,200 Speaker 1: did it. I mean, I just, oh, yeah, calculated risk. 931 00:51:12,400 --> 00:51:14,319 Speaker 1: I thought it was fun. You know, people don't need 932 00:51:14,360 --> 00:51:16,560 Speaker 1: to know who I am. The people who I originally 933 00:51:16,719 --> 00:51:20,480 Speaker 1: sent it to knew who I was. The when Tanta 934 00:51:20,560 --> 00:51:24,799 Speaker 1: came on board, Tanta was very concerned. She was very 935 00:51:24,880 --> 00:51:27,880 Speaker 1: obviously very hopeful that she would recover, so she wanted 936 00:51:27,920 --> 00:51:30,319 Speaker 1: to maintain and she she was very concerned if she 937 00:51:30,360 --> 00:51:34,200 Speaker 1: said certain things, she may never get another job. And actually, 938 00:51:34,200 --> 00:51:37,440 Speaker 1: people in the industry knew who she was immediately. Yeah, 939 00:51:37,480 --> 00:51:39,640 Speaker 1: there's only so many people that could be writing what 940 00:51:39,719 --> 00:51:43,319 Speaker 1: she wrote, and uh and and then there are very 941 00:51:43,320 --> 00:51:46,680 Speaker 1: few of those were women, so so uh uh. But 942 00:51:46,760 --> 00:51:48,719 Speaker 1: so you know, then as long as she wanted to 943 00:51:48,760 --> 00:51:51,040 Speaker 1: stay anonymous, I stayed anonymous too. I didn't want pressure 944 00:51:51,080 --> 00:51:54,759 Speaker 1: on her. And so, um, the first time my name 945 00:51:54,840 --> 00:51:57,719 Speaker 1: actually came out was in the obituary in the New 946 00:51:57,800 --> 00:52:01,120 Speaker 1: York Times. Really for Tanta no kidding. That was the 947 00:52:01,120 --> 00:52:03,000 Speaker 1: first time. I believe that was the first time my 948 00:52:03,120 --> 00:52:05,759 Speaker 1: name came out. Uh. And then after that, my name 949 00:52:05,800 --> 00:52:07,560 Speaker 1: is in the open. So I went ahead and just 950 00:52:07,600 --> 00:52:10,759 Speaker 1: started saying yeah. And that was pretty much because they 951 00:52:10,800 --> 00:52:13,120 Speaker 1: quoted me in the New York Times talking about Tante 952 00:52:13,880 --> 00:52:16,000 Speaker 1: and obviously they had her real name in that article too. 953 00:52:16,239 --> 00:52:19,000 Speaker 1: So I posted on the blog, asked calculator risk anything, 954 00:52:19,080 --> 00:52:21,839 Speaker 1: he's a little blast for the pet from the past. Yeah, 955 00:52:21,880 --> 00:52:24,439 Speaker 1: I look at that. I pulled the old header from 956 00:52:24,480 --> 00:52:28,200 Speaker 1: the blog spot days. Yeah, I like I like that picture. 957 00:52:28,200 --> 00:52:30,560 Speaker 1: I like that picture. I always like that. The path 958 00:52:30,680 --> 00:52:32,640 Speaker 1: right down the middle between the trees. I took that 959 00:52:32,800 --> 00:52:36,880 Speaker 1: up in Canada. That that's really so you guys can 960 00:52:36,920 --> 00:52:40,799 Speaker 1: see that on on the big picture. So the anonymity 961 00:52:40,840 --> 00:52:43,520 Speaker 1: just kind of ended. It ended when Tonta passed away. 962 00:52:43,680 --> 00:52:47,120 Speaker 1: It just it wasn't a conscious decision. Soon as soon 963 00:52:47,160 --> 00:52:49,200 Speaker 1: as she passed away, my name was in public anyway. 964 00:52:49,200 --> 00:52:50,960 Speaker 1: I I you know, I obviously linked to the New 965 00:52:51,040 --> 00:52:55,560 Speaker 1: York Times the Bituari, which was actually a lovely, lovely 966 00:52:56,160 --> 00:53:00,200 Speaker 1: it was they wrote a beautiful piece and and and 967 00:53:00,239 --> 00:53:02,839 Speaker 1: I think that's probably the first time anyone got im 968 00:53:02,880 --> 00:53:05,759 Speaker 1: obituary for being a blogger. She was so famous. I 969 00:53:06,120 --> 00:53:08,520 Speaker 1: think that that might very well be the case. So 970 00:53:08,600 --> 00:53:13,200 Speaker 1: let's talk about a related issue. What is the war 971 00:53:13,360 --> 00:53:18,680 Speaker 1: on data? I wrote a piece I don't know last 972 00:53:18,719 --> 00:53:22,160 Speaker 1: month or whenever that was the Bookmarke did and saved 973 00:53:22,160 --> 00:53:25,120 Speaker 1: it knowing this was coming up. By the way, for listeners, 974 00:53:26,080 --> 00:53:28,359 Speaker 1: Bill lives on the other side, literally about as far 975 00:53:28,400 --> 00:53:31,680 Speaker 1: away in mainland, United States. You're in Newport Beach, and 976 00:53:33,040 --> 00:53:36,440 Speaker 1: we knew you were coming in five months ago, four 977 00:53:36,480 --> 00:53:39,640 Speaker 1: months ago. So I started saying saving stuff. Oh, let 978 00:53:39,640 --> 00:53:42,239 Speaker 1: me ask him about this. That one has been with 979 00:53:42,280 --> 00:53:45,319 Speaker 1: me for a while, So let's let's jump into it. 980 00:53:45,480 --> 00:53:48,239 Speaker 1: What what is the war on data? Well, it's we 981 00:53:48,239 --> 00:53:52,920 Speaker 1: were talking about a little bit earlier. Um is there's 982 00:53:53,360 --> 00:53:55,920 Speaker 1: a sense that the data is false by a certain 983 00:53:55,920 --> 00:54:00,800 Speaker 1: group of people, not just the employment not just flogyment data, 984 00:54:00,840 --> 00:54:02,799 Speaker 1: but but they they you know, I'd have to go 985 00:54:02,880 --> 00:54:05,399 Speaker 1: back through my piece, but I forget all the things 986 00:54:05,400 --> 00:54:07,759 Speaker 1: I was pulling out. Some of it's political, some of 987 00:54:07,800 --> 00:54:11,400 Speaker 1: it's with people with positions, I mean market positions or 988 00:54:11,440 --> 00:54:14,440 Speaker 1: housing positions. Yeah, they're just there. There's there are a 989 00:54:14,520 --> 00:54:18,120 Speaker 1: group of people. It's just like people that reject climate change. 990 00:54:18,160 --> 00:54:20,520 Speaker 1: If you will, you know, uh, what do you say 991 00:54:20,520 --> 00:54:24,319 Speaker 1: in climate change is real? Now I gotta go, I 992 00:54:24,360 --> 00:54:27,480 Speaker 1: gotta go rethink everything. Um. But you know, there's there 993 00:54:27,480 --> 00:54:30,520 Speaker 1: are people that are that are rejecting data and going 994 00:54:30,560 --> 00:54:32,959 Speaker 1: with what they want it to be. The data wanted. 995 00:54:33,080 --> 00:54:35,439 Speaker 1: They want the data to be this for whatever reason, 996 00:54:35,440 --> 00:54:39,080 Speaker 1: whether it's political or or cognitive dissonance. Yeah, I think 997 00:54:40,080 --> 00:54:43,360 Speaker 1: I think some percentage of these folks don't even realize 998 00:54:43,400 --> 00:54:46,040 Speaker 1: what they're doing. Some are just outright lyne but there's 999 00:54:46,080 --> 00:54:50,600 Speaker 1: a healthy percentage that simply can't acknowledge well or or 1000 00:54:50,680 --> 00:54:54,479 Speaker 1: they see their own circumstances and and maybe believe that 1001 00:54:54,480 --> 00:54:57,760 Speaker 1: that's more widespread. You know, maybe maybe for whatever reason, 1002 00:54:57,760 --> 00:55:01,719 Speaker 1: they're seeing more inflation than the inflation data shows and 1003 00:55:02,120 --> 00:55:05,160 Speaker 1: because of where, how how they spend their money. Uh, 1004 00:55:05,680 --> 00:55:09,400 Speaker 1: you know, no question, rent's gone up faster than than inflation. 1005 00:55:09,520 --> 00:55:11,800 Speaker 1: So if a rent, if a rents a big portion 1006 00:55:11,880 --> 00:55:14,239 Speaker 1: of somebody's monthly spending, they're going to think what those 1007 00:55:14,280 --> 00:55:17,440 Speaker 1: inflation numbers are are incorrect. So, you know, there's some 1008 00:55:17,520 --> 00:55:20,200 Speaker 1: of that. It's just that I think people are taking 1009 00:55:20,239 --> 00:55:23,560 Speaker 1: that people in positions of of of some power are 1010 00:55:23,560 --> 00:55:27,600 Speaker 1: taking that and or or commentators and and just attacking 1011 00:55:27,680 --> 00:55:30,560 Speaker 1: data right and left. And you know, if if like 1012 00:55:31,160 --> 00:55:34,080 Speaker 1: we were talking earlier, you you have to have a 1013 00:55:34,080 --> 00:55:35,960 Speaker 1: good system of collecting data and you have to be 1014 00:55:36,000 --> 00:55:38,600 Speaker 1: transparent on the data. And that's what we have at 1015 00:55:38,640 --> 00:55:40,920 Speaker 1: the United States probably has the best data in the world. 1016 00:55:41,160 --> 00:55:43,520 Speaker 1: But who's even close. There's no one even said well, 1017 00:55:43,600 --> 00:55:47,759 Speaker 1: Western Europe is far behind us, and um um. And 1018 00:55:47,840 --> 00:55:51,799 Speaker 1: at dinner last night a reporter who is hometown in 1019 00:55:51,840 --> 00:55:54,840 Speaker 1: London was saying, the UK has terrible data competed in 1020 00:55:54,840 --> 00:55:56,919 Speaker 1: the United States. Yeah, I mean and and and they're 1021 00:55:57,080 --> 00:56:00,000 Speaker 1: and they're actually very good. It's you know, in the world. 1022 00:56:00,000 --> 00:56:02,600 Speaker 1: World in the United States is just excellent. And well 1023 00:56:02,600 --> 00:56:05,440 Speaker 1: we started post recession and post Great Depression in the 1024 00:56:05,560 --> 00:56:09,560 Speaker 1: thirties and forties. This really came about, um from from 1025 00:56:09,600 --> 00:56:12,160 Speaker 1: a number of people where it was pretty clear there 1026 00:56:12,280 --> 00:56:15,799 Speaker 1: was no data to measure progress or lack thereof. Well, 1027 00:56:15,840 --> 00:56:18,480 Speaker 1: you know that anytime you have something that you want 1028 00:56:18,520 --> 00:56:20,480 Speaker 1: to understand, you have, the first thing you have to 1029 00:56:20,520 --> 00:56:23,560 Speaker 1: do is measure it. Uh and and because then if 1030 00:56:23,600 --> 00:56:25,520 Speaker 1: you say you make a policy change, well, how do 1031 00:56:25,560 --> 00:56:28,920 Speaker 1: you know if it did anything? If if you're if 1032 00:56:28,920 --> 00:56:30,759 Speaker 1: you can't measure it, and it's like it's like, you know, 1033 00:56:30,840 --> 00:56:32,720 Speaker 1: losing weight or something. If you don't get on the scale, 1034 00:56:33,000 --> 00:56:34,360 Speaker 1: how do you know if you've really lost weight? I 1035 00:56:34,360 --> 00:56:38,120 Speaker 1: guess you could check. Yeah, but that's another measurement system. 1036 00:56:38,160 --> 00:56:42,040 Speaker 1: I guess it is. Yeah. So um, yes, After the 1037 00:56:42,040 --> 00:56:45,600 Speaker 1: Great Depression, they started doing really collecting much better employment data. 1038 00:56:45,960 --> 00:56:49,080 Speaker 1: I was kind of hoping after the Great Recession that 1039 00:56:49,200 --> 00:56:52,239 Speaker 1: there would be an emphasis on collecting better housing data. 1040 00:56:52,280 --> 00:56:54,719 Speaker 1: I think they could improve the housing data in what way? 1041 00:56:54,920 --> 00:56:56,920 Speaker 1: So so we have so let's go over some of 1042 00:56:56,920 --> 00:56:59,960 Speaker 1: the housing stats. So you have the existing home sale, 1043 00:57:00,160 --> 00:57:04,200 Speaker 1: which is reported by the National Association of Realtors. You 1044 00:57:04,280 --> 00:57:08,680 Speaker 1: have a new home sales, which is UH Census Department 1045 00:57:08,760 --> 00:57:12,520 Speaker 1: Bureau UM, which is sort of kind of self reported 1046 00:57:12,560 --> 00:57:17,840 Speaker 1: by the builders themselves well independently, independently. And I recall 1047 00:57:17,960 --> 00:57:19,840 Speaker 1: writing something that you can want to take a three 1048 00:57:19,880 --> 00:57:22,160 Speaker 1: month average anytime you have an outlier to the upside 1049 00:57:22,240 --> 00:57:26,680 Speaker 1: or outside and invariably flip reverses the fire. That's right, 1050 00:57:26,720 --> 00:57:29,080 Speaker 1: we had a huge upside. Yeah, yeah, I would, I would. 1051 00:57:29,080 --> 00:57:31,320 Speaker 1: I would say, hey, it's great, it's a great, great number. 1052 00:57:31,760 --> 00:57:35,680 Speaker 1: I wouldn't say, yeah, yeah, that's that's And if you 1053 00:57:35,720 --> 00:57:37,600 Speaker 1: go back and look at the data, you can always 1054 00:57:37,640 --> 00:57:40,720 Speaker 1: spot the outlier and the month the following, because what 1055 00:57:40,840 --> 00:57:42,840 Speaker 1: ends up happening is people, well they'll revise that down 1056 00:57:43,360 --> 00:57:46,400 Speaker 1: and and the whatever follows it will be a terrible month, 1057 00:57:46,720 --> 00:57:49,360 Speaker 1: and that will eventually get get revised up. And that's 1058 00:57:50,200 --> 00:57:52,880 Speaker 1: one of the reasons I do graphs anyway. It is 1059 00:57:52,880 --> 00:57:55,040 Speaker 1: because it kind of can show you where you're at. Yeah, 1060 00:57:55,080 --> 00:57:57,080 Speaker 1: this would be a little spike up and and but 1061 00:57:57,160 --> 00:58:00,880 Speaker 1: it's within the range of variability. We're getting there anyway. 1062 00:58:00,920 --> 00:58:04,120 Speaker 1: I you know, it's only six fifty, that's not even 1063 00:58:04,160 --> 00:58:06,440 Speaker 1: that big of a number. So that's right. So, so 1064 00:58:06,560 --> 00:58:08,800 Speaker 1: we have new home sales, we have existing home sales, 1065 00:58:08,880 --> 00:58:13,800 Speaker 1: we have contract signings, we have permits for for building 1066 00:58:14,320 --> 00:58:19,320 Speaker 1: housing starts. Is a very important number. Why is that? Um, well, 1067 00:58:20,400 --> 00:58:22,920 Speaker 1: that's one of the biggest impacts on the economy is 1068 00:58:23,000 --> 00:58:26,600 Speaker 1: how many from the housing industry as opposed to existing 1069 00:58:26,640 --> 00:58:32,360 Speaker 1: home sales. Existing home sales is just there's a mortgageys. Yeah, 1070 00:58:32,400 --> 00:58:36,840 Speaker 1: that's the Yes, people do frequently buy a little more furniture. 1071 00:58:37,960 --> 00:58:40,800 Speaker 1: But but but it's it's more from the direct sale. 1072 00:58:40,880 --> 00:58:42,480 Speaker 1: That's all it is is the broker's fee and a 1073 00:58:42,520 --> 00:58:45,400 Speaker 1: few other fees mortgages. That adds to the economy. But 1074 00:58:45,480 --> 00:58:47,840 Speaker 1: when you build a new home sales, the whole prices 1075 00:58:48,520 --> 00:58:50,880 Speaker 1: is new. It's that you've added to the existing wealth 1076 00:58:50,920 --> 00:58:53,520 Speaker 1: of the company, the country. Uh so it's it's a 1077 00:58:53,600 --> 00:58:56,360 Speaker 1: big deal. And what's the ratio of existing to new 1078 00:58:56,440 --> 00:59:01,640 Speaker 1: home sales more or less? Uh, it's about eight to one, 1079 00:59:02,920 --> 00:59:05,520 Speaker 1: maybe tend to one, even he used to it used 1080 00:59:05,560 --> 00:59:09,040 Speaker 1: to be closer maybe six to one existing to the new. 1081 00:59:09,640 --> 00:59:14,520 Speaker 1: Um there's there's been ever since the crisis, a lot 1082 00:59:14,600 --> 00:59:17,919 Speaker 1: more existing home sales. New homes got slaughtered. Well, because 1083 00:59:18,000 --> 00:59:22,880 Speaker 1: you're you're competing against foreclosures, you're competing against dramatically. Although 1084 00:59:22,960 --> 00:59:26,200 Speaker 1: let's talk a little bit about foreclosures and and before 1085 00:59:26,240 --> 00:59:29,680 Speaker 1: I get to foreclosures, I almost forgot multi family homes. 1086 00:59:29,960 --> 00:59:33,560 Speaker 1: That's been a big uptick post crisis. Also, yes, And 1087 00:59:33,800 --> 00:59:37,400 Speaker 1: is that just a reflection of rental demand or well? Yeah, Well, 1088 00:59:37,480 --> 00:59:39,760 Speaker 1: you know, one of the nice things about for multi 1089 00:59:39,840 --> 00:59:44,520 Speaker 1: family is there's the demographics have been incredibly positive for him. 1090 00:59:45,080 --> 00:59:47,600 Speaker 1: At the same time you had all these people moving 1091 00:59:47,680 --> 00:59:51,280 Speaker 1: out of foreclosed homes, and and and looking for a 1092 00:59:51,280 --> 00:59:53,200 Speaker 1: place to rent. Now, a lot of those houses were 1093 00:59:53,400 --> 00:59:56,480 Speaker 1: bought to to rent, and so that you would think, oh, well, 1094 00:59:56,520 --> 00:59:58,560 Speaker 1: would you wouldn't have this multi family But but you 1095 00:59:58,640 --> 01:00:01,120 Speaker 1: do have this huge surge in people in the twenties 1096 01:00:01,760 --> 01:00:05,600 Speaker 1: and that's the main rental a demographic. So there's a 1097 01:00:05,640 --> 01:00:08,560 Speaker 1: big cohort there. They're not going to buy. There's well 1098 01:00:08,560 --> 01:00:10,960 Speaker 1: they're starting to move into the buying years. So we 1099 01:00:11,160 --> 01:00:14,840 Speaker 1: were moving out of parents basement. They're certainly renting. Are 1100 01:00:14,920 --> 01:00:17,720 Speaker 1: they forming households? That's another great data. Yeah, and they 1101 01:00:17,760 --> 01:00:20,760 Speaker 1: will household formation and they will and and uh, you 1102 01:00:20,840 --> 01:00:23,280 Speaker 1: know the problem with household formation data. See, there's an 1103 01:00:23,320 --> 01:00:26,040 Speaker 1: area that we could really improve is everybody uses the 1104 01:00:26,240 --> 01:00:30,760 Speaker 1: HVS Housing Vacancy Survey or whatever and and uh, and 1105 01:00:30,960 --> 01:00:36,120 Speaker 1: that data is not consistent with with the annual census 1106 01:00:36,240 --> 01:00:40,200 Speaker 1: or the ten year census. So and the Census Bureau 1107 01:00:40,280 --> 01:00:42,240 Speaker 1: is aware of that and they're trying to figure out 1108 01:00:42,360 --> 01:00:46,000 Speaker 1: why that data is so inconsistent. Um, but that's something 1109 01:00:46,080 --> 01:00:48,240 Speaker 1: they can do a much better job of, I think 1110 01:00:48,360 --> 01:00:51,680 Speaker 1: is is uh household formations. So the next president gets 1111 01:00:51,720 --> 01:00:54,800 Speaker 1: elected and they say, I want to see some better 1112 01:00:55,640 --> 01:00:58,600 Speaker 1: data on the economics side, and they pick up the 1113 01:00:58,640 --> 01:01:00,880 Speaker 1: phone and say, Bill, you mind coming to d C 1114 01:01:01,080 --> 01:01:02,640 Speaker 1: for a year or two. We have some work for you. 1115 01:01:03,560 --> 01:01:07,800 Speaker 1: What sort of stuff would you would you look to add, refine, improve, 1116 01:01:08,120 --> 01:01:13,080 Speaker 1: or eliminate. Well, I think housing is is so important 1117 01:01:13,360 --> 01:01:15,760 Speaker 1: that I would definitely go through the methodology of each 1118 01:01:15,840 --> 01:01:19,040 Speaker 1: of those. Um. One of the interesting things I think 1119 01:01:19,280 --> 01:01:24,480 Speaker 1: is h for housing starts. If I'm remembering this correctly, 1120 01:01:24,520 --> 01:01:28,920 Speaker 1: it might be new home sales, they don't include certain condos, right, 1121 01:01:29,280 --> 01:01:31,800 Speaker 1: so if if if if they're side by side condos, 1122 01:01:31,840 --> 01:01:34,160 Speaker 1: they include them. But if their high right condo condos, 1123 01:01:34,200 --> 01:01:38,280 Speaker 1: they don't. And it's really complicated, and and and there's there, 1124 01:01:38,640 --> 01:01:41,240 Speaker 1: and we're moving to where there's more of those being built, 1125 01:01:41,760 --> 01:01:44,800 Speaker 1: so we could have more units coming on the market 1126 01:01:44,840 --> 01:01:47,240 Speaker 1: than anybody's really aware. That has to be fixed. Yeah, 1127 01:01:47,320 --> 01:01:49,680 Speaker 1: that that just needs to be resolved. What what aren't 1128 01:01:49,720 --> 01:01:55,400 Speaker 1: we measuring that we should? Well, you know, I I'm 1129 01:01:55,480 --> 01:02:00,320 Speaker 1: not completely confident in the private sources of of data. 1130 01:02:00,560 --> 01:02:03,440 Speaker 1: So let's talk about the National Association of Realtors and 1131 01:02:03,480 --> 01:02:05,800 Speaker 1: I'll throw them under the bus because I know you 1132 01:02:05,840 --> 01:02:09,920 Speaker 1: don't want to do that. We all so everybody who 1133 01:02:10,080 --> 01:02:14,880 Speaker 1: blogged about realistic and economics used to make fun of 1134 01:02:15,000 --> 01:02:18,400 Speaker 1: the chief economists for the n R because they were 1135 01:02:19,240 --> 01:02:21,920 Speaker 1: from the peak and oh six to the bottom in 1136 01:02:23,040 --> 01:02:26,640 Speaker 1: they were just relentlessly optimistic. And I figured that guy's 1137 01:02:26,680 --> 01:02:31,959 Speaker 1: named David David Young, that's the current guy. Um Laria. Yeah, 1138 01:02:32,720 --> 01:02:38,000 Speaker 1: so he had the same book. So the fantastic thing 1139 01:02:38,040 --> 01:02:41,000 Speaker 1: about that book is the same book came out two 1140 01:02:41,120 --> 01:02:45,040 Speaker 1: or three times, same picture, same everything. This is a 1141 01:02:45,080 --> 01:02:48,040 Speaker 1: blog post somewhere about it. And they just changed the 1142 01:02:48,160 --> 01:02:50,520 Speaker 1: name of it. So the first name was something like 1143 01:02:51,440 --> 01:02:53,080 Speaker 1: I'll google it and see if I can find it. 1144 01:02:53,160 --> 01:02:55,200 Speaker 1: Why now is the time to buy housing? It was 1145 01:02:55,280 --> 01:02:58,080 Speaker 1: right at the peak, and then two years later they 1146 01:02:58,400 --> 01:03:01,360 Speaker 1: reissued it with a different house and take advantage of 1147 01:03:01,480 --> 01:03:05,360 Speaker 1: the decline in housing. And then the third the third 1148 01:03:05,640 --> 01:03:08,200 Speaker 1: cover was We're all going to die run for the 1149 01:03:08,320 --> 01:03:10,600 Speaker 1: hills sort of thing. And and by the way, that 1150 01:03:10,800 --> 01:03:14,280 Speaker 1: was at the bottom. It was it was quite quite amazing. Well, 1151 01:03:14,360 --> 01:03:16,880 Speaker 1: you know when we're talking about than are you know, 1152 01:03:17,080 --> 01:03:18,960 Speaker 1: I have a good relationship with a lot of the 1153 01:03:19,080 --> 01:03:24,560 Speaker 1: industry people at nb A Mortgage Bankers Association, which I 1154 01:03:24,800 --> 01:03:27,360 Speaker 1: find to be a much more realistic Those guys are. 1155 01:03:27,440 --> 01:03:29,400 Speaker 1: They're straight shooters and and they and they do an 1156 01:03:29,440 --> 01:03:32,200 Speaker 1: excellent job. National Associated Homebuilders same thing than are For 1157 01:03:32,320 --> 01:03:35,520 Speaker 1: some reason, they're more cheerleader oriented because it's it's real 1158 01:03:35,640 --> 01:03:39,000 Speaker 1: estate agents and uh and and uh here it is. 1159 01:03:39,080 --> 01:03:42,800 Speaker 1: I actually found it the O five, Um, David Laria, 1160 01:03:43,280 --> 01:03:47,120 Speaker 1: are you missing the real estate Boom? And then and 1161 01:03:47,240 --> 01:03:49,960 Speaker 1: then um the second version of the cover in two 1162 01:03:50,040 --> 01:03:52,760 Speaker 1: thousand and six was why the real Estate Boom Will 1163 01:03:52,800 --> 01:03:55,840 Speaker 1: Not Bust? And then the two thousand and seven and 1164 01:03:56,040 --> 01:03:59,080 Speaker 1: by the way, there's a house floating and a couple 1165 01:03:59,160 --> 01:04:01,280 Speaker 1: with a kid looking at it. In the first two editions. 1166 01:04:01,720 --> 01:04:04,080 Speaker 1: The third edition, All real estate is local. The house 1167 01:04:04,200 --> 01:04:08,200 Speaker 1: is missing, it's just at and that is actually, this 1168 01:04:08,480 --> 01:04:12,520 Speaker 1: is not fabricated. This is true. It's the same book. 1169 01:04:13,960 --> 01:04:17,040 Speaker 1: You know, could not have been more wrong with with 1170 01:04:17,200 --> 01:04:21,800 Speaker 1: three different covers. It's quite it's quite uh quite astonishing. 1171 01:04:22,240 --> 01:04:25,200 Speaker 1: But their role is a cheerleader, right, I mean National 1172 01:04:25,240 --> 01:04:29,440 Speaker 1: Associated Homebuilder their role they they they they're the homebuilders 1173 01:04:29,480 --> 01:04:31,760 Speaker 1: really want to know what's happening, and so when they 1174 01:04:31,840 --> 01:04:34,960 Speaker 1: gather data from them and distribute it, it's real. And 1175 01:04:35,120 --> 01:04:37,840 Speaker 1: same with Mortgage Bankers Association. I'm not saying the NORDS 1176 01:04:37,960 --> 01:04:41,600 Speaker 1: data isn't real. They just they they spin it. They 1177 01:04:41,640 --> 01:04:44,840 Speaker 1: spent it very positively, and it's not really gathered in 1178 01:04:44,960 --> 01:04:49,200 Speaker 1: a very scientific way. So, um, so isn't it based 1179 01:04:49,280 --> 01:04:55,040 Speaker 1: on on on what McCall it on? Actual closings? Don't they? Yeah? 1180 01:04:55,120 --> 01:04:57,600 Speaker 1: But you know they they're they're sampling. It's mushy, Yeah, 1181 01:04:57,640 --> 01:05:00,400 Speaker 1: they were. They sample. What they do is they sample 1182 01:05:00,520 --> 01:05:04,920 Speaker 1: certain large multiple listing services and that's they based it 1183 01:05:05,120 --> 01:05:07,320 Speaker 1: off that. And then every what they were doing is 1184 01:05:07,360 --> 01:05:10,200 Speaker 1: every ten years they would go to the Census Bureau 1185 01:05:10,640 --> 01:05:12,680 Speaker 1: and and look at how many houses have sold, and 1186 01:05:12,720 --> 01:05:16,200 Speaker 1: then they would try to rejigger. Yeah, if you will, 1187 01:05:16,480 --> 01:05:19,160 Speaker 1: so and so I I to me, you know, we're 1188 01:05:19,200 --> 01:05:21,800 Speaker 1: getting to the stage where why can't we count pretty 1189 01:05:21,880 --> 01:05:24,920 Speaker 1: much every closing in America? I don't understand why not either? Yeah, 1190 01:05:24,920 --> 01:05:27,960 Speaker 1: I mean, I I so that I know that's been discussed. 1191 01:05:28,080 --> 01:05:30,520 Speaker 1: When you're in DC. Can we get the BLS or 1192 01:05:31,120 --> 01:05:34,560 Speaker 1: i'd really Commerce Department? I like I'd like to see 1193 01:05:34,600 --> 01:05:36,880 Speaker 1: them do that. And and you know the other thing 1194 01:05:37,000 --> 01:05:41,040 Speaker 1: is is when they're calculating GDP, they're just estimating the 1195 01:05:41,120 --> 01:05:45,480 Speaker 1: percentage that the salesperson gets and which has been under pressure, 1196 01:05:45,520 --> 01:05:48,440 Speaker 1: and it's actually yeah, and and and I think that, 1197 01:05:49,040 --> 01:05:52,040 Speaker 1: you know, it's very possible that that's being overstated a 1198 01:05:52,120 --> 01:05:54,200 Speaker 1: little bit. So we really who knows, who knows? I 1199 01:05:54,280 --> 01:05:56,600 Speaker 1: really don't know. Nobody knows. And and uh, I mean 1200 01:05:56,640 --> 01:05:59,000 Speaker 1: there's a lot of estimating that goes on, but that 1201 01:05:59,240 --> 01:06:02,920 Speaker 1: that whole industry is undergoing dramatic change right now. And 1202 01:06:03,160 --> 01:06:05,760 Speaker 1: and uh, you know the online sites have just changed 1203 01:06:05,840 --> 01:06:08,720 Speaker 1: it dramatically, so you you, you know, they could measure 1204 01:06:08,760 --> 01:06:11,800 Speaker 1: that a lot better. And and so we've talked about 1205 01:06:11,880 --> 01:06:15,600 Speaker 1: how they commit. They might be missing some high rise condos. 1206 01:06:16,160 --> 01:06:19,800 Speaker 1: The the existing home sales and commissions I think could 1207 01:06:19,840 --> 01:06:23,240 Speaker 1: be measured a lot better. Um house prices I think 1208 01:06:23,360 --> 01:06:25,760 Speaker 1: is an interesting thing. The f h f A. It 1209 01:06:25,840 --> 01:06:28,920 Speaker 1: does an excellent job, and they have an expanded series, 1210 01:06:29,280 --> 01:06:32,280 Speaker 1: it doesn't get the publicity it deserves. Are they tracking 1211 01:06:32,360 --> 01:06:35,720 Speaker 1: the same house over time? Yes, exactly. So that's what's 1212 01:06:35,800 --> 01:06:39,520 Speaker 1: really fascinating. Supposed to repeat sales. But you know, even 1213 01:06:39,680 --> 01:06:43,240 Speaker 1: even that, you know it's right away seven years apart 1214 01:06:43,280 --> 01:06:45,840 Speaker 1: on average something like that. Yeah, something like that. And 1215 01:06:46,040 --> 01:06:49,560 Speaker 1: but you know, even that has obvious flaws. What if 1216 01:06:49,600 --> 01:06:51,280 Speaker 1: the people didn't maintain it what if they put in 1217 01:06:51,360 --> 01:06:53,800 Speaker 1: a new kitchen, you know, uh so just put it 1218 01:06:53,840 --> 01:06:56,120 Speaker 1: in the bathroom. Yeah, they and they try and and 1219 01:06:56,320 --> 01:06:59,280 Speaker 1: they try to do some permitting. It was something permitted, 1220 01:06:59,320 --> 01:07:00,520 Speaker 1: but you know a lot of people put in a 1221 01:07:00,520 --> 01:07:04,400 Speaker 1: new bathroom without permitting it and nephews. So in my 1222 01:07:05,720 --> 01:07:09,760 Speaker 1: town of Oyster Bay, unless you're changing the footprint of 1223 01:07:10,080 --> 01:07:13,680 Speaker 1: the house or running a natural gas line in like 1224 01:07:13,920 --> 01:07:16,200 Speaker 1: I'm in the midst of doing, you don't need a permit. 1225 01:07:16,560 --> 01:07:19,400 Speaker 1: A permit for the natural gas. You could redo a kitchen, 1226 01:07:19,440 --> 01:07:21,080 Speaker 1: you could redo a bathroom. You don't need a permit. 1227 01:07:21,480 --> 01:07:23,720 Speaker 1: If you if you extend the house, if you change 1228 01:07:23,720 --> 01:07:26,680 Speaker 1: the footprint, if you replace a make a deck bigger, 1229 01:07:27,560 --> 01:07:30,080 Speaker 1: and it impinges on the name, you you need a permit. 1230 01:07:30,240 --> 01:07:32,520 Speaker 1: But you know, it depends on what you do. Obviously. 1231 01:07:32,640 --> 01:07:35,640 Speaker 1: I think in any area you can retile your bathroom 1232 01:07:36,160 --> 01:07:39,640 Speaker 1: without a permit. I think if you move the electricity around, yep, 1233 01:07:39,880 --> 01:07:42,760 Speaker 1: change the plugs, whatever, I think most places would require 1234 01:07:42,800 --> 01:07:45,680 Speaker 1: a permit. Makes sense. You have to have the electrical 1235 01:07:45,760 --> 01:07:49,520 Speaker 1: inspector to make sure it was done to so, you know, 1236 01:07:49,640 --> 01:07:51,840 Speaker 1: But but a lot of people do that without permits. 1237 01:07:52,000 --> 01:07:54,120 Speaker 1: So there's because you don't want to pay an increased 1238 01:07:54,160 --> 01:07:56,160 Speaker 1: tax rate. You pay a fine at the end five 1239 01:07:56,240 --> 01:07:58,720 Speaker 1: years later, so instead of paying a thousand dollars more 1240 01:07:58,720 --> 01:08:00,840 Speaker 1: a year, you pay two. They never they never even 1241 01:08:00,880 --> 01:08:03,880 Speaker 1: catch them. Sometimes you need a CEO, a certificate of 1242 01:08:03,960 --> 01:08:07,400 Speaker 1: ocupancy when you do the sale, so people run around 1243 01:08:07,440 --> 01:08:10,400 Speaker 1: before a closing in order to make all that um 1244 01:08:10,880 --> 01:08:14,080 Speaker 1: On the spin from the National Association of Realtors, I'm 1245 01:08:14,160 --> 01:08:17,280 Speaker 1: going way back two thousand and seven, there was a 1246 01:08:17,439 --> 01:08:21,280 Speaker 1: quote in the Palm Beach Post. Some realtors are grumbling 1247 01:08:21,320 --> 01:08:25,400 Speaker 1: about prices falling. Guess who they're not falling. Guess who 1248 01:08:25,439 --> 01:08:28,599 Speaker 1: they're blaming. A growing number of realtors in Florida are 1249 01:08:28,640 --> 01:08:32,560 Speaker 1: frustrated with the state and National Realtors Group efforts to 1250 01:08:32,840 --> 01:08:36,400 Speaker 1: spin the market as one that is strengthening and where 1251 01:08:36,439 --> 01:08:40,799 Speaker 1: home prices are stabilizing. We people can take Customers continue 1252 01:08:40,840 --> 01:08:43,680 Speaker 1: to list their homes at prices that are unrealistic, and 1253 01:08:43,800 --> 01:08:47,360 Speaker 1: as a result, sales volumes and thus commissions continue to 1254 01:08:47,400 --> 01:08:50,160 Speaker 1: be depressed. So the net impact of the n a 1255 01:08:50,280 --> 01:08:53,639 Speaker 1: R spin in oh seven was that agents were saying 1256 01:08:53,680 --> 01:08:58,080 Speaker 1: to people, these prices are unrealistic, and they're saying, well, 1257 01:08:58,120 --> 01:09:00,800 Speaker 1: I read the paper. Things are getting better. Yeah, that's 1258 01:09:00,840 --> 01:09:03,680 Speaker 1: the problem. That's what the home builders don't tolerate. But 1259 01:09:03,800 --> 01:09:07,400 Speaker 1: the agents, but on a national level have have mess wet. Yeah, 1260 01:09:07,520 --> 01:09:10,080 Speaker 1: you know, but there's there's more than the National Association 1261 01:09:10,080 --> 01:09:14,320 Speaker 1: of Realtors there they're compliding about. And if you own yeah, 1262 01:09:14,520 --> 01:09:16,679 Speaker 1: well they are clearly. But if you if you own 1263 01:09:16,720 --> 01:09:19,639 Speaker 1: a home and it's pretty much equivalent to your neighbor 1264 01:09:19,720 --> 01:09:22,439 Speaker 1: and he sold it for six hundred thousand, and the 1265 01:09:22,520 --> 01:09:24,800 Speaker 1: agents tell you when you're only gonna get five hundred thousand. 1266 01:09:24,840 --> 01:09:28,439 Speaker 1: For years, you think that agents crazy. And and yet 1267 01:09:28,560 --> 01:09:31,160 Speaker 1: that might have been a very fair price or maybe 1268 01:09:31,200 --> 01:09:33,400 Speaker 1: even too high. How many times did you have that 1269 01:09:33,640 --> 01:09:37,200 Speaker 1: conversation with people and they said, when did the neighbors 1270 01:09:37,240 --> 01:09:39,880 Speaker 1: sell the house? Well they sold it to know five. Well, 1271 01:09:39,920 --> 01:09:43,679 Speaker 1: it's oh eight and we have five million foreclosures exactly. 1272 01:09:44,439 --> 01:09:46,080 Speaker 1: If you want to sell at that price, getting a 1273 01:09:46,160 --> 01:09:49,040 Speaker 1: time machine, go back to oh five, you get that price. Yeah, 1274 01:09:49,280 --> 01:09:51,880 Speaker 1: but you have to. It does take extra effort. You 1275 01:09:51,960 --> 01:09:53,760 Speaker 1: do have to explain that to him and go through. 1276 01:09:54,080 --> 01:09:58,040 Speaker 1: I do know a family member, my mom, who wanted 1277 01:09:58,120 --> 01:10:01,439 Speaker 1: to sell in like two thousands heaven and uh and 1278 01:10:01,840 --> 01:10:04,280 Speaker 1: moved to a retirement community and it worked out great 1279 01:10:04,320 --> 01:10:06,120 Speaker 1: for her. But I I went down, we went and 1280 01:10:06,200 --> 01:10:08,519 Speaker 1: looked at the local houses and they were the inventory 1281 01:10:08,680 --> 01:10:12,040 Speaker 1: was really expanding, and I said, let's underprice everybody, and 1282 01:10:12,360 --> 01:10:14,680 Speaker 1: and uh and we sold it right away and and 1283 01:10:14,840 --> 01:10:16,479 Speaker 1: and you know what, that guy's got a nice house 1284 01:10:16,520 --> 01:10:18,160 Speaker 1: and it's worth more than he paid for it. So 1285 01:10:18,640 --> 01:10:21,000 Speaker 1: ten years later and yeah, he's he's fine, and he 1286 01:10:21,160 --> 01:10:23,479 Speaker 1: and you know, he loves the house. And but my 1287 01:10:23,600 --> 01:10:26,519 Speaker 1: mom got that money out. It made her her retirement easy, 1288 01:10:27,080 --> 01:10:29,639 Speaker 1: you know. But other people were sticking to their prices, 1289 01:10:29,720 --> 01:10:31,920 Speaker 1: you know, and or chasing them down, which is probably 1290 01:10:31,920 --> 01:10:34,160 Speaker 1: the worst thing you can do. I did that with 1291 01:10:34,280 --> 01:10:37,880 Speaker 1: a house we tried to buy, and thanks to technology, 1292 01:10:37,960 --> 01:10:41,160 Speaker 1: you could look at every listing price and then you 1293 01:10:41,240 --> 01:10:43,840 Speaker 1: find out so it's here, and then it's a hundred 1294 01:10:43,880 --> 01:10:45,960 Speaker 1: thousand lower, and then it's a hundred thousand lower, and 1295 01:10:46,520 --> 01:10:49,519 Speaker 1: you're watching them, but they're a hundred thousand or more 1296 01:10:50,120 --> 01:10:52,800 Speaker 1: behind the market, so they're just following it down and 1297 01:10:52,880 --> 01:10:55,360 Speaker 1: not selling it and just creating this paper trail. Or 1298 01:10:55,400 --> 01:10:56,960 Speaker 1: chasing the market is one of the worst things you 1299 01:10:57,000 --> 01:10:58,920 Speaker 1: can do. You gotta skate to where the puck is 1300 01:10:58,920 --> 01:11:01,040 Speaker 1: gonna be not to where it was five minutes ago. 1301 01:11:01,560 --> 01:11:04,680 Speaker 1: And really, you know, selling a house is so emotional. Hey, 1302 01:11:04,760 --> 01:11:07,120 Speaker 1: we lived here for twenty years, we raised our kids here. 1303 01:11:07,439 --> 01:11:09,840 Speaker 1: How could this only be worth x? It's worth three 1304 01:11:10,120 --> 01:11:12,760 Speaker 1: X well to you, but you've already bought it. You've 1305 01:11:12,800 --> 01:11:16,120 Speaker 1: gotta it's coming to somebody who doesn't have the memories. 1306 01:11:16,160 --> 01:11:20,760 Speaker 1: You gotta get realistic. So we mentioned foreclosures before. Let's 1307 01:11:20,800 --> 01:11:25,519 Speaker 1: talk a little bit about the foreclosure crisis way back when. Um, 1308 01:11:26,479 --> 01:11:29,800 Speaker 1: what took place, uh during the from the O six 1309 01:11:29,880 --> 01:11:35,240 Speaker 1: peak to bottom more or less? Um? And what did 1310 01:11:35,320 --> 01:11:37,160 Speaker 1: we do right as a country and what are we 1311 01:11:37,200 --> 01:11:40,680 Speaker 1: doing wrong with that? You know, I personally think it's 1312 01:11:42,160 --> 01:11:45,519 Speaker 1: some areas of the country are still trying to recover. 1313 01:11:45,800 --> 01:11:50,840 Speaker 1: So New Jersey, but that has that New Jersey has 1314 01:11:50,880 --> 01:11:54,479 Speaker 1: its own specific Yeah. But but you know, but if 1315 01:11:54,520 --> 01:11:57,400 Speaker 1: you go and look the states that have been slowest 1316 01:11:57,479 --> 01:12:01,960 Speaker 1: to recover all have judicial foreclosures them. That's taken forever. Yeah, 1317 01:12:02,000 --> 01:12:04,120 Speaker 1: and and you know by half the states are judicial. 1318 01:12:04,120 --> 01:12:06,680 Speaker 1: You gotta go to court. The other states, it's it's 1319 01:12:07,240 --> 01:12:10,080 Speaker 1: a straightforward system. What about the rocket courts that Florida 1320 01:12:10,120 --> 01:12:13,000 Speaker 1: set up yeah, you know, I guess they've supposed to 1321 01:12:13,000 --> 01:12:15,720 Speaker 1: be horrible by the way, I'm sure because people have 1322 01:12:15,960 --> 01:12:18,240 Speaker 1: complained that they haven't even gotten noticed they've come home 1323 01:12:18,320 --> 01:12:21,439 Speaker 1: and well, you know that it really didn't help. It 1324 01:12:21,520 --> 01:12:24,200 Speaker 1: made things obviously much much worse for everybody that the 1325 01:12:24,240 --> 01:12:27,360 Speaker 1: mortgage industry was cheating on the foreclosures constantly. Yeah, and 1326 01:12:27,439 --> 01:12:31,719 Speaker 1: so ham Bondi, a g of of Attorney General of Florida, 1327 01:12:31,840 --> 01:12:35,000 Speaker 1: got elected and stopped but with a lot of real 1328 01:12:35,120 --> 01:12:39,559 Speaker 1: estate developer and real estate owners backings, and stopped all 1329 01:12:39,640 --> 01:12:45,040 Speaker 1: the mortgage foreclosure cheating investigations that her office her predecessor 1330 01:12:45,160 --> 01:12:48,240 Speaker 1: Edward not my favorite age in America. Yeah, but that 1331 01:12:48,439 --> 01:12:50,760 Speaker 1: you know, to me, that that was that made things 1332 01:12:50,840 --> 01:12:54,080 Speaker 1: a much much worse. Is if if they had just 1333 01:12:54,200 --> 01:12:57,640 Speaker 1: followed the rules and and done things correctly, what do 1334 01:12:57,680 --> 01:12:59,840 Speaker 1: you do when you can't find a note. We're missing 1335 01:12:59,880 --> 01:13:03,400 Speaker 1: the note? Now, well you can always go recreated. I mean, 1336 01:13:03,840 --> 01:13:05,960 Speaker 1: but they were paying there was actually I could cost 1337 01:13:06,040 --> 01:13:07,400 Speaker 1: you a lot of money. That's one of the things 1338 01:13:07,479 --> 01:13:10,400 Speaker 1: that Tanta was talking about. They they had cut the 1339 01:13:10,479 --> 01:13:14,000 Speaker 1: back rooms so much that they that whole they just 1340 01:13:14,080 --> 01:13:16,200 Speaker 1: kind of assumed, well, we're never going to have foreclosures, 1341 01:13:16,560 --> 01:13:20,120 Speaker 1: you know where when when Tanta was working in that industry, 1342 01:13:20,200 --> 01:13:22,599 Speaker 1: that was very important to check every file, to make 1343 01:13:22,640 --> 01:13:25,559 Speaker 1: sure every file was completely correct. You know, you had 1344 01:13:25,600 --> 01:13:27,880 Speaker 1: all every single piece of document, which is what they 1345 01:13:27,920 --> 01:13:30,840 Speaker 1: do again today. So so what about let's talk a 1346 01:13:30,880 --> 01:13:35,880 Speaker 1: little bit about MERS the Mortgage Electronic Registry. I like 1347 01:13:36,040 --> 01:13:38,479 Speaker 1: the idea. I think it's greatly see I think that 1348 01:13:38,640 --> 01:13:42,879 Speaker 1: it's a scam and it exists to not pay recording 1349 01:13:42,960 --> 01:13:46,679 Speaker 1: tax or transfer tax county by county. They've been sued 1350 01:13:46,720 --> 01:13:49,479 Speaker 1: by a number of people. Well I I yes, but 1351 01:13:50,400 --> 01:13:53,040 Speaker 1: and it allows you to to put you could sell 1352 01:13:53,080 --> 01:13:56,800 Speaker 1: a mortgage so many times that supposedly you're tracking it 1353 01:13:56,840 --> 01:13:59,800 Speaker 1: through this electronic registry, but you weren't. There was some 1354 01:14:00,000 --> 01:14:02,160 Speaker 1: any times we didn't couldn't tell who won't the house. Well, 1355 01:14:02,200 --> 01:14:05,920 Speaker 1: first of all, it was implemented poorly. Once it's implemented poorly, 1356 01:14:05,960 --> 01:14:08,719 Speaker 1: it's a bad system. So you don't there's no argument 1357 01:14:08,760 --> 01:14:11,400 Speaker 1: for me on that. The general idea. I kind of like, 1358 01:14:11,920 --> 01:14:15,920 Speaker 1: well if it was done with full congressional authority and 1359 01:14:16,120 --> 01:14:19,200 Speaker 1: local authority, but that didn't happen. I mean, I mean 1360 01:14:19,280 --> 01:14:22,479 Speaker 1: the idea of that that you because because what they 1361 01:14:22,520 --> 01:14:24,880 Speaker 1: wanted to do was put the mortgage the mortgages into 1362 01:14:24,960 --> 01:14:27,600 Speaker 1: mortgage backed security. Sure, and nothing wrong with that. No, 1363 01:14:27,680 --> 01:14:29,719 Speaker 1: it's nothing wrong with that, But it's gotta you can't 1364 01:14:29,880 --> 01:14:33,519 Speaker 1: have just some random companies saying wouldn't in my opinion, 1365 01:14:33,600 --> 01:14:37,559 Speaker 1: we can't bypass the local authority because it's faster, easier, cheaper. 1366 01:14:38,120 --> 01:14:42,040 Speaker 1: I'm convinced that mirrors is an underwritten story of the crisis. 1367 01:14:42,560 --> 01:14:45,000 Speaker 1: But for mers, we may not have had as deep 1368 01:14:45,040 --> 01:14:47,719 Speaker 1: and bed. You couldn't have cranked out as many houses 1369 01:14:47,760 --> 01:14:50,120 Speaker 1: and as No, yeah you need you needed to that. Yeah, 1370 01:14:50,520 --> 01:14:52,240 Speaker 1: So so that was that was you know, it was 1371 01:14:52,240 --> 01:14:54,280 Speaker 1: a little bit of a grease enabler. But we want 1372 01:14:54,320 --> 01:14:57,280 Speaker 1: your cause, so sure. No, definitely not a cause, but 1373 01:14:57,520 --> 01:15:01,400 Speaker 1: definitely an enabler. God, there's so many questions I haven't 1374 01:15:01,439 --> 01:15:03,800 Speaker 1: gotten to and I want to make sure I leave 1375 01:15:04,040 --> 01:15:09,000 Speaker 1: leave some time to our standard questions. Um. So here's 1376 01:15:09,000 --> 01:15:12,240 Speaker 1: an interesting question A reader had asked. Asked McBride what 1377 01:15:12,439 --> 01:15:16,120 Speaker 1: policy choices he would make to improve a lot of 1378 01:15:16,240 --> 01:15:24,200 Speaker 1: the bottom even if it hurt corporate America. Well, uh 1379 01:15:24,560 --> 01:15:27,120 Speaker 1: not not. You know, I think that one of the 1380 01:15:27,200 --> 01:15:29,439 Speaker 1: key things is is you've got to have wages up. 1381 01:15:29,600 --> 01:15:32,080 Speaker 1: You have to get wages up for the lower income workers. 1382 01:15:32,360 --> 01:15:34,680 Speaker 1: So how do we do that? And so with the 1383 01:15:35,720 --> 01:15:38,120 Speaker 1: the to one thing you can do is you can 1384 01:15:38,160 --> 01:15:41,720 Speaker 1: mandate a higher a minimum wage. That will help. How 1385 01:15:41,760 --> 01:15:44,280 Speaker 1: many people earned minimum wage? It's not that many, but 1386 01:15:44,360 --> 01:15:46,240 Speaker 1: it pushes up the people that are just above minimum 1387 01:15:46,720 --> 01:15:51,600 Speaker 1: I guess everybody. And then but but I think the 1388 01:15:51,680 --> 01:15:55,320 Speaker 1: key is more bargaining power for workers of some sort. 1389 01:15:55,520 --> 01:15:58,760 Speaker 1: So that means stronger unions. Yeah, well we've crushed the unions, yes, 1390 01:15:58,920 --> 01:16:01,800 Speaker 1: other than the public union um, which which have plenty 1391 01:16:01,800 --> 01:16:04,000 Speaker 1: of problems still, you know, I mean because they have 1392 01:16:04,080 --> 01:16:07,800 Speaker 1: all these pensions that are crazy. So with the public unions, 1393 01:16:07,840 --> 01:16:09,720 Speaker 1: I'm kind of like, well, we should take a lot 1394 01:16:09,800 --> 01:16:13,240 Speaker 1: of effort and and and work on those the pensions. 1395 01:16:13,320 --> 01:16:15,800 Speaker 1: But but if when we're talking about improving a lot 1396 01:16:15,880 --> 01:16:19,800 Speaker 1: of the lower fift I think getting some sort of 1397 01:16:19,880 --> 01:16:25,440 Speaker 1: bargaining for workers, um and you know, whether they're unionized 1398 01:16:25,520 --> 01:16:27,680 Speaker 1: or some other way. I'm not a labor expert, but 1399 01:16:27,720 --> 01:16:29,439 Speaker 1: I do think that that's where one of the keys. 1400 01:16:29,960 --> 01:16:33,439 Speaker 1: The the full of the may be a coincidence, but 1401 01:16:33,600 --> 01:16:37,280 Speaker 1: the full of the strength of unions and the full 1402 01:16:37,520 --> 01:16:42,240 Speaker 1: and middle class income is seems to be quite the coincidence. 1403 01:16:42,360 --> 01:16:45,360 Speaker 1: One would imagine they're related. Oh, they're They're definitely related, 1404 01:16:45,400 --> 01:16:48,479 Speaker 1: there's no question. And in raising the minimum wage is 1405 01:16:48,520 --> 01:16:51,000 Speaker 1: going to help some. So you know, there's a policy 1406 01:16:51,080 --> 01:16:54,360 Speaker 1: that we can do. I don't think that there's a 1407 01:16:54,400 --> 01:16:56,800 Speaker 1: big negative impact for for I mean, for you know, 1408 01:16:57,160 --> 01:16:59,479 Speaker 1: in most areas, especially in the course if you look right, 1409 01:16:59,520 --> 01:17:02,720 Speaker 1: if you look in the Seattle and Portland and San 1410 01:17:02,800 --> 01:17:05,639 Speaker 1: Francisco in l A, they could raise a minimum wage 1411 01:17:05,640 --> 01:17:08,040 Speaker 1: to fifteen dollars and it's fine, may not work in 1412 01:17:08,120 --> 01:17:10,120 Speaker 1: the heartland. Yeah, basically in l A you had to 1413 01:17:10,120 --> 01:17:14,200 Speaker 1: pay that anyway. So um, well, you see Walmart McDonald's 1414 01:17:14,240 --> 01:17:18,040 Speaker 1: raising the minimum that's telling you they're having trouble getting workers. 1415 01:17:18,479 --> 01:17:20,400 Speaker 1: So so it's it's how you can either let the 1416 01:17:20,479 --> 01:17:24,240 Speaker 1: market do it or speed along and do it legislatively. 1417 01:17:24,280 --> 01:17:26,559 Speaker 1: I know a lot of people have a mandate. Yeah, 1418 01:17:26,640 --> 01:17:28,960 Speaker 1: I mean, working for the minimum wage is pretty minimal. 1419 01:17:29,600 --> 01:17:32,920 Speaker 1: And you're at even at at fifteen dollars, you're still 1420 01:17:33,280 --> 01:17:36,320 Speaker 1: at a at a forty hour week, you're you're more 1421 01:17:36,439 --> 01:17:38,519 Speaker 1: or less right at the poverty level, depending on how 1422 01:17:38,560 --> 01:17:40,120 Speaker 1: many kids. I don't know, how you live in l 1423 01:17:40,200 --> 01:17:42,679 Speaker 1: A or New York can It's it's impossible. You've taken 1424 01:17:42,720 --> 01:17:46,120 Speaker 1: a second job working off the books. It's it's rough. Uh. 1425 01:17:46,479 --> 01:17:50,160 Speaker 1: Interesting question that came in from another reader. Um, we 1426 01:17:50,360 --> 01:17:54,240 Speaker 1: keep hearing about quote the next subprime. Where do you 1427 01:17:54,320 --> 01:17:57,960 Speaker 1: see excesses in the credit market that might be the 1428 01:17:58,080 --> 01:18:02,680 Speaker 1: next subprime? You know? Right now? It's I I think 1429 01:18:02,720 --> 01:18:06,360 Speaker 1: we're okay in most areas. Um. I mean a lot 1430 01:18:06,400 --> 01:18:08,400 Speaker 1: of people focus on the auto loans, but you know 1431 01:18:08,439 --> 01:18:11,280 Speaker 1: auto loans at car the cars are easy to repossess. 1432 01:18:11,680 --> 01:18:14,599 Speaker 1: The technology that's built into it now is you buy 1433 01:18:14,640 --> 01:18:17,000 Speaker 1: a car if you don't have a good credit rating. 1434 01:18:17,320 --> 01:18:19,080 Speaker 1: I wrote a column about this a few months ago. 1435 01:18:19,800 --> 01:18:23,000 Speaker 1: And they building a remote kill switch, so you miss 1436 01:18:23,120 --> 01:18:25,479 Speaker 1: a payment, they shut the car off. Yeah, people, you 1437 01:18:25,560 --> 01:18:27,679 Speaker 1: want that car, you gotta water the money. And yeah 1438 01:18:27,920 --> 01:18:31,760 Speaker 1: in in l A, you want your car bad for sure. 1439 01:18:32,040 --> 01:18:33,799 Speaker 1: That's how you get to work or get to anything. 1440 01:18:33,920 --> 01:18:37,160 Speaker 1: So you know, people pay. During the four closure crisis, 1441 01:18:37,200 --> 01:18:39,320 Speaker 1: people were paying their car loans, but they weren't paying 1442 01:18:39,360 --> 01:18:42,000 Speaker 1: their house loans. The story was you'd pay your visa, 1443 01:18:42,080 --> 01:18:45,160 Speaker 1: you'd pay your car loan, you would skip the student loan. 1444 01:18:45,240 --> 01:18:47,439 Speaker 1: You would skip the mortgage because what are they gonna do. 1445 01:18:47,479 --> 01:18:49,720 Speaker 1: It's gonna take three years. Yeah, you know, I'm not 1446 01:18:49,960 --> 01:18:53,040 Speaker 1: I'm not that concerned about student loans either. I I 1447 01:18:53,200 --> 01:18:57,400 Speaker 1: think that there's things we can do, um, lower interest rates. Sure, 1448 01:18:57,640 --> 01:19:00,920 Speaker 1: I I you know, when I went to school cool, Um, 1449 01:19:01,320 --> 01:19:03,960 Speaker 1: you know, it really dates me. But I paid. I 1450 01:19:04,000 --> 01:19:07,719 Speaker 1: went to University of California, Irvine. Paid two hundred dollars 1451 01:19:07,760 --> 01:19:10,519 Speaker 1: a quarter to go to school. I went to Sunny 1452 01:19:10,520 --> 01:19:13,400 Speaker 1: Stony Brook. My first semester was semester, not even quarter. 1453 01:19:13,479 --> 01:19:17,479 Speaker 1: Two semesters four fifty. Yeah, so you know, uh, I 1454 01:19:17,600 --> 01:19:20,040 Speaker 1: could go. I paid my way through school. I could 1455 01:19:20,120 --> 01:19:23,960 Speaker 1: work on the weekends, pay my rent, pay my my tuition. 1456 01:19:24,080 --> 01:19:26,479 Speaker 1: I think that that's kind of Now it's twelve thousand 1457 01:19:26,560 --> 01:19:28,439 Speaker 1: a semester. What do you do? Yeah, I mean, if 1458 01:19:28,439 --> 01:19:30,160 Speaker 1: you can't work on the weekends to go to school, 1459 01:19:30,720 --> 01:19:33,639 Speaker 1: it makes life completely different. Sure, you know, not everybody 1460 01:19:33,720 --> 01:19:35,559 Speaker 1: did that. Luckily, a lot of people when I was young, 1461 01:19:35,680 --> 01:19:37,720 Speaker 1: their parents paid it because it wasn't that much either, 1462 01:19:37,840 --> 01:19:40,280 Speaker 1: you know. But so you know there's I do like 1463 01:19:40,439 --> 01:19:46,080 Speaker 1: the idea of making some education less expensive makes sense. What, um, 1464 01:19:46,240 --> 01:19:49,720 Speaker 1: what asset classes do you see as expensive or is 1465 01:19:49,760 --> 01:19:53,640 Speaker 1: that something you really don't pay close attention to. Um, 1466 01:19:54,520 --> 01:19:57,560 Speaker 1: you know, I I I know it's not something I 1467 01:19:57,640 --> 01:20:02,519 Speaker 1: don't write about. But you basically everything is at least 1468 01:20:02,560 --> 01:20:05,760 Speaker 1: fairly valued now I don't see you know, like in 1469 01:20:05,880 --> 01:20:08,559 Speaker 1: two thousand twelve, it was clear to me that if 1470 01:20:08,720 --> 01:20:10,599 Speaker 1: you should be out buying as much real estate as 1471 01:20:10,640 --> 01:20:16,400 Speaker 1: you could, um, the in two thousand nine, you should 1472 01:20:16,439 --> 01:20:18,080 Speaker 1: be jumping in as hard as you can into the 1473 01:20:18,120 --> 01:20:25,160 Speaker 1: stock market. So what do you do in two thousand six, Um, Well, 1474 01:20:25,240 --> 01:20:26,920 Speaker 1: earlier this year I did buy. I put some money 1475 01:20:26,920 --> 01:20:30,120 Speaker 1: into the stock market when we had that nice yeah, 1476 01:20:30,240 --> 01:20:32,679 Speaker 1: and and so that was well, you know, luckily I'm 1477 01:20:32,680 --> 01:20:34,160 Speaker 1: not sitting on any cash right now. I don't know 1478 01:20:34,240 --> 01:20:36,360 Speaker 1: exactly what I would do today. You know, It's funny. 1479 01:20:36,400 --> 01:20:37,840 Speaker 1: One of the things is I don't know what I'm 1480 01:20:37,880 --> 01:20:41,160 Speaker 1: gonna do until I need to do it exactly. Uh. 1481 01:20:41,920 --> 01:20:45,680 Speaker 1: I like that. I don't give advice on investing on 1482 01:20:45,720 --> 01:20:48,120 Speaker 1: a daily basis. You know, back when, because we were 1483 01:20:48,160 --> 01:20:52,080 Speaker 1: talking about the commenting and I participated in this site 1484 01:20:52,120 --> 01:20:56,160 Speaker 1: called Silicon Investor for a little while. And they, by 1485 01:20:56,200 --> 01:20:58,559 Speaker 1: the way, they came to fame in the late nineties 1486 01:20:58,640 --> 01:21:02,639 Speaker 1: screaming bubble, and they were right eventually, but getting timing 1487 01:21:02,720 --> 01:21:05,320 Speaker 1: on that is really you know, we would talk with 1488 01:21:05,479 --> 01:21:08,280 Speaker 1: some you know, as as happens on every commenting thing. 1489 01:21:08,400 --> 01:21:11,120 Speaker 1: At first it was really good, and uh we talk 1490 01:21:11,160 --> 01:21:14,720 Speaker 1: about different stocks and and uh. One of the things 1491 01:21:14,760 --> 01:21:16,840 Speaker 1: I discovered at the time is I could mention ten 1492 01:21:16,920 --> 01:21:19,720 Speaker 1: stocks that I thought were good, and nine of them 1493 01:21:19,760 --> 01:21:22,280 Speaker 1: would do great and one of them would really underperform. 1494 01:21:22,920 --> 01:21:25,479 Speaker 1: And then people, every time I would say anything, people 1495 01:21:25,520 --> 01:21:28,360 Speaker 1: come back, weren't you the one who liked x y Z? Yes? 1496 01:21:28,479 --> 01:21:30,519 Speaker 1: Out of the ten stocks I mentioned x Y And 1497 01:21:30,600 --> 01:21:32,960 Speaker 1: after a while you go, I'm tired of this, you know, 1498 01:21:33,200 --> 01:21:36,360 Speaker 1: I let's let's chase let's chase away all the good 1499 01:21:36,439 --> 01:21:39,000 Speaker 1: commenters and just get it to the point where it's 1500 01:21:39,040 --> 01:21:41,280 Speaker 1: just garbage. And that's what they do. The nice thing 1501 01:21:41,360 --> 01:21:43,519 Speaker 1: about you have an NBA. The nice thing about law 1502 01:21:43,600 --> 01:21:46,639 Speaker 1: school is you learn the rules of rhetoric and debate, 1503 01:21:47,120 --> 01:21:50,080 Speaker 1: and so you could very I can very quickly identify 1504 01:21:50,840 --> 01:21:53,200 Speaker 1: that's a strong man argument, that's an ad hominum attack, 1505 01:21:53,320 --> 01:21:56,240 Speaker 1: that's arguing from extreme that's all right, Like you start 1506 01:21:56,320 --> 01:22:00,840 Speaker 1: to notice all than not and comments are us they're 1507 01:22:00,840 --> 01:22:05,679 Speaker 1: all that. It's just a place where logic and reasoning 1508 01:22:05,800 --> 01:22:09,720 Speaker 1: go to die. It's unfortunate. So last question before I 1509 01:22:09,800 --> 01:22:14,280 Speaker 1: get to my standard questions. I asked everybody so you 1510 01:22:14,360 --> 01:22:19,519 Speaker 1: said you don't see a recession anytime um soon? And 1511 01:22:19,640 --> 01:22:22,639 Speaker 1: I never asked people for what where, what's your favorite stock, 1512 01:22:22,800 --> 01:22:24,519 Speaker 1: what's what's your with is the market could be what's 1513 01:22:24,560 --> 01:22:28,160 Speaker 1: your forecast? So I'm reluctant to ask this as a 1514 01:22:28,280 --> 01:22:32,680 Speaker 1: forecasting question. But how long? So I'm gonna phrase it 1515 01:22:32,720 --> 01:22:38,520 Speaker 1: slightly differently. How long do you see this economic expansion continuing? 1516 01:22:39,240 --> 01:22:42,479 Speaker 1: Is this something that could go on for eight thirty 1517 01:22:42,560 --> 01:22:45,519 Speaker 1: six months or a wee closer to the end of 1518 01:22:45,560 --> 01:22:48,479 Speaker 1: the cycle than we are to the beginning. Oh, I 1519 01:22:48,680 --> 01:22:50,439 Speaker 1: would say we're probably closer to the end in the 1520 01:22:50,520 --> 01:22:54,000 Speaker 1: beginning because we've been this seven years, seven years, it 1521 01:22:54,120 --> 01:22:57,479 Speaker 1: will go another seven years. It could actually because because 1522 01:22:57,520 --> 01:23:03,240 Speaker 1: of the slow growth. I don't think it's gonna have Yeah, 1523 01:23:03,280 --> 01:23:05,000 Speaker 1: I don't think that's going to happen. But you know, 1524 01:23:05,120 --> 01:23:08,080 Speaker 1: you look around, look at mortgage I could be withdrawal 1525 01:23:08,720 --> 01:23:11,960 Speaker 1: is still basically zero. You know people are really yeah 1526 01:23:12,160 --> 01:23:14,240 Speaker 1: people you we used to we used to look at 1527 01:23:14,280 --> 01:23:17,479 Speaker 1: that data point. It was. It was enormously you know, 1528 01:23:17,840 --> 01:23:20,680 Speaker 1: people are pouring money out of their houses, you know, 1529 01:23:20,920 --> 01:23:22,840 Speaker 1: and and yeah, we're I think we're I think we're 1530 01:23:22,920 --> 01:23:25,640 Speaker 1: right at that starting to turn positive again. But that 1531 01:23:25,760 --> 01:23:28,680 Speaker 1: can go a long time positive. So you know, the 1532 01:23:28,880 --> 01:23:31,360 Speaker 1: in the economy, so so I you know, as far 1533 01:23:31,439 --> 01:23:36,320 Speaker 1: as the cycle, I think we're mid cycle somewhere, maybe 1534 01:23:36,439 --> 01:23:40,240 Speaker 1: late in mid cycle. I'm of that camp that sixth inning, 1535 01:23:40,640 --> 01:23:42,680 Speaker 1: that metaphor no but no, yeah, but I'm I'm of 1536 01:23:42,880 --> 01:23:45,920 Speaker 1: the camp that they recovers, don't expansions, don't die of 1537 01:23:46,000 --> 01:23:48,960 Speaker 1: old age, they die for other reasons. And so we 1538 01:23:49,080 --> 01:23:52,160 Speaker 1: need to see some real excesses. Um. You know, some 1539 01:23:52,280 --> 01:23:56,280 Speaker 1: people it's easy to point out excesses, uh you or 1540 01:23:56,439 --> 01:23:58,400 Speaker 1: or imagined excesses. You could say, well, look at the 1541 01:23:58,439 --> 01:24:00,800 Speaker 1: bond market. The bond deals are so low. Clearly that's 1542 01:24:00,800 --> 01:24:04,280 Speaker 1: going to blow up someday. Yeah. But I mean I'm 1543 01:24:04,320 --> 01:24:06,280 Speaker 1: not I'm not so I'm not in that camp. I 1544 01:24:06,560 --> 01:24:10,439 Speaker 1: I think that we're not seeing the excess as yet. 1545 01:24:10,479 --> 01:24:13,080 Speaker 1: We're not seeing the inflation that the Fed really would 1546 01:24:13,120 --> 01:24:15,280 Speaker 1: need to fight. I think that's going to be slow 1547 01:24:15,360 --> 01:24:19,479 Speaker 1: to come. Um, the demographics is improving, in the US. Um, 1548 01:24:20,400 --> 01:24:22,840 Speaker 1: you know, they forget about the baby boomers, they're moving on. 1549 01:24:23,760 --> 01:24:25,640 Speaker 1: But we're getting that nice group in the in the 1550 01:24:25,720 --> 01:24:29,640 Speaker 1: twenties or gen X, gen y, Yeah, millennials and and 1551 01:24:29,760 --> 01:24:31,920 Speaker 1: don't and and you know there there could be a 1552 01:24:32,040 --> 01:24:35,519 Speaker 1: little bit more inflation as they compete for products. But 1553 01:24:35,760 --> 01:24:38,200 Speaker 1: but you know, I don't see it picking up dramatically 1554 01:24:38,280 --> 01:24:40,360 Speaker 1: like we saw in the seventies at all. All right, 1555 01:24:40,439 --> 01:24:43,439 Speaker 1: so let's jump into my standard questions. Already told us 1556 01:24:43,439 --> 01:24:49,479 Speaker 1: about your background. Who are your early mentors, um as 1557 01:24:49,560 --> 01:24:56,200 Speaker 1: far as economics as anything. Uh, I was very fortunate 1558 01:24:56,320 --> 01:24:59,080 Speaker 1: to have some very good CEOs that I worked with, 1559 01:25:00,120 --> 01:25:04,120 Speaker 1: Don Judgen. Don Judson at vital Com, I was absolutely 1560 01:25:04,120 --> 01:25:07,160 Speaker 1: brilliant guy. Uh. I was kind of the number two 1561 01:25:07,200 --> 01:25:10,120 Speaker 1: guy there for for a number of years. Um, you know, 1562 01:25:10,200 --> 01:25:13,960 Speaker 1: he just he just would see things and and uh 1563 01:25:14,560 --> 01:25:18,960 Speaker 1: and so he was great. And uh Don Barry two Dons, 1564 01:25:19,080 --> 01:25:23,280 Speaker 1: the two Dons was at the at the telecommunications company. 1565 01:25:23,320 --> 01:25:26,439 Speaker 1: He was the founder of that and just another brilliant, 1566 01:25:26,520 --> 01:25:29,200 Speaker 1: positive person you know who just was a hard worker. 1567 01:25:30,160 --> 01:25:33,760 Speaker 1: Both those guys really promoted my career. Um. So yeah, 1568 01:25:34,600 --> 01:25:36,600 Speaker 1: those those two guys, I want a lot to the 1569 01:25:37,000 --> 01:25:42,680 Speaker 1: two dons. How about investors, any particular investor influence your 1570 01:25:42,720 --> 01:25:48,320 Speaker 1: approach to investing, be at real estate stocks whatever, um 1571 01:25:50,360 --> 01:25:53,240 Speaker 1: some Warren Buffett. I can't go wrong with that. Yeah, 1572 01:25:53,360 --> 01:25:57,240 Speaker 1: so uh could do us. Yeah on real estate, you 1573 01:25:57,280 --> 01:26:01,040 Speaker 1: know a little bit. My dad Uh uh, you know 1574 01:26:01,200 --> 01:26:04,400 Speaker 1: that's nice. My dad, My dad had. My dad's still around. 1575 01:26:04,400 --> 01:26:06,719 Speaker 1: He's ninety four. So he got to see the blog 1576 01:26:06,840 --> 01:26:08,840 Speaker 1: blow up. He got to yeah, you're all of your 1577 01:26:09,400 --> 01:26:12,639 Speaker 1: post career success. He must have appreciated that. It's funny 1578 01:26:12,680 --> 01:26:15,040 Speaker 1: because it's the only what's the only thing he ever 1579 01:26:15,080 --> 01:26:17,840 Speaker 1: really understood that I did. Really he come and see 1580 01:26:18,000 --> 01:26:19,560 Speaker 1: he come and look at the heart monitors and go, 1581 01:26:19,680 --> 01:26:22,160 Speaker 1: what the heck is this all a that that that 1582 01:26:22,360 --> 01:26:24,640 Speaker 1: you know when I started writing the blog. He understood that. 1583 01:26:25,240 --> 01:26:27,160 Speaker 1: And uh but he you know, he had he had 1584 01:26:27,320 --> 01:26:30,439 Speaker 1: some funny sayings. One was, the deal of the century 1585 01:26:30,479 --> 01:26:33,400 Speaker 1: comes along every year, so you know you don't have 1586 01:26:33,479 --> 01:26:35,639 Speaker 1: to like a year, flood comes along every five Yeah, 1587 01:26:35,680 --> 01:26:37,439 Speaker 1: you don't have to. You don't have to jump on anything. 1588 01:26:37,640 --> 01:26:40,800 Speaker 1: There'll be another good opportunity six months from now or 1589 01:26:40,800 --> 01:26:42,840 Speaker 1: a year from now. He goes on the deal. Deal 1590 01:26:42,880 --> 01:26:46,680 Speaker 1: of the century comes along every years. Um, let's talk 1591 01:26:46,680 --> 01:26:49,080 Speaker 1: about books. What are some of your favorite books, be 1592 01:26:49,280 --> 01:26:52,800 Speaker 1: they economic or otherwise, fiction or nonfictional. Well, I just 1593 01:26:53,000 --> 01:26:56,640 Speaker 1: finished reading, Um, well I can I'll mention a few 1594 01:26:56,680 --> 01:27:01,200 Speaker 1: economic books. Um. A book called Big Ship Ahead, Big 1595 01:27:01,520 --> 01:27:04,479 Speaker 1: Shifts Ahead. Yeah. I don't have the whole title, but 1596 01:27:04,640 --> 01:27:06,600 Speaker 1: that's the first person on the side. Yeah, it's a 1597 01:27:06,960 --> 01:27:09,680 Speaker 1: it's I don't know if it's available yet. I read 1598 01:27:09,720 --> 01:27:13,880 Speaker 1: a preview. It's by Chris Porter and John Burns, both 1599 01:27:13,960 --> 01:27:18,400 Speaker 1: real estate guys. And Chris Porter's a demographic guy. And uh, 1600 01:27:18,720 --> 01:27:21,200 Speaker 1: and this is really driven by democrat like Harry Dent 1601 01:27:21,360 --> 01:27:24,560 Speaker 1: used to be Mr Demography. Yeah, well this book is 1602 01:27:24,600 --> 01:27:29,280 Speaker 1: about the shifting demographics and what it means for businesses 1603 01:27:29,439 --> 01:27:32,280 Speaker 1: and primarily for the real estate industry and housing. And 1604 01:27:32,360 --> 01:27:34,760 Speaker 1: you enjoyed it and and yeah, because it's it's something 1605 01:27:34,880 --> 01:27:37,960 Speaker 1: I think that that's very very important to understand. And 1606 01:27:38,360 --> 01:27:40,760 Speaker 1: uh and you know what, how people are going to 1607 01:27:40,800 --> 01:27:44,320 Speaker 1: be building different projects. Um. And I think they did 1608 01:27:44,320 --> 01:27:47,479 Speaker 1: a really good job. It was very interesting to me. Um. 1609 01:27:48,080 --> 01:27:53,360 Speaker 1: But else I really liked. Um. Uh, let me think, 1610 01:27:53,720 --> 01:27:58,800 Speaker 1: what's the house of debt? House of debt? I could 1611 01:27:59,000 --> 01:28:02,960 Speaker 1: see and I could see it sitting on my bookshelf 1612 01:28:03,479 --> 01:28:08,439 Speaker 1: on the and yeah, and uh and dr she's in 1613 01:28:08,520 --> 01:28:13,400 Speaker 1: California somewhere right or or he he's I think he's 1614 01:28:13,880 --> 01:28:16,800 Speaker 1: in the Midwest. I'm thinking of a different book then. Yeah, 1615 01:28:16,960 --> 01:28:20,640 Speaker 1: but it's got like the torn sort of page of 1616 01:28:20,920 --> 01:28:23,160 Speaker 1: of I'm trying to remember what the cover looks like. 1617 01:28:23,280 --> 01:28:24,960 Speaker 1: But House of Debt, and you can look that one up. 1618 01:28:25,040 --> 01:28:27,720 Speaker 1: House of Debt, all right, okay? And that that what 1619 01:28:27,880 --> 01:28:31,000 Speaker 1: they did with the two professors. What they did is 1620 01:28:31,080 --> 01:28:36,120 Speaker 1: they looked at micro data in available in each city 1621 01:28:36,200 --> 01:28:39,800 Speaker 1: to see how much um people, how much household debt 1622 01:28:39,880 --> 01:28:43,840 Speaker 1: people had, and how that related to the strength of 1623 01:28:43,920 --> 01:28:45,960 Speaker 1: the recovery or the depth of the recession. And it 1624 01:28:46,120 --> 01:28:49,800 Speaker 1: was very very interesting and very insightful. So you know, 1625 01:28:49,880 --> 01:28:52,400 Speaker 1: the more people could borrow, obviously, the more more trouble 1626 01:28:52,439 --> 01:28:54,800 Speaker 1: they got into House of Debt. How they and you 1627 01:28:54,960 --> 01:28:59,439 Speaker 1: caused the Great Recession? Can prevent it from happening again? 1628 01:29:00,040 --> 01:29:04,200 Speaker 1: A mir Sufi and a tief me on, yes, all right. 1629 01:29:04,479 --> 01:29:09,280 Speaker 1: And the other one was called Big Shifts, Big Shifts 1630 01:29:09,320 --> 01:29:13,200 Speaker 1: Ahead by Porter and Burns John Burns and Chris Border. 1631 01:29:13,640 --> 01:29:18,000 Speaker 1: Big Shifts Ahead Demographic Clarity for business that's not coming 1632 01:29:18,000 --> 01:29:20,479 Speaker 1: out until October. Give me one more. What else have 1633 01:29:20,560 --> 01:29:24,160 Speaker 1: you read that you've really enjoyed? Uh? The kersh Act 1634 01:29:24,840 --> 01:29:28,479 Speaker 1: Ben Bernink? Oh? Really? Yeah? I thought that was fun. 1635 01:29:29,360 --> 01:29:31,840 Speaker 1: You know, it's interesting because it's just from his perspective. Now, 1636 01:29:31,920 --> 01:29:34,200 Speaker 1: you and I were writing about, you know, anything that 1637 01:29:34,360 --> 01:29:39,040 Speaker 1: that's um about the crisis, the courage to act, a 1638 01:29:39,080 --> 01:29:42,080 Speaker 1: memoir of a crisis and its aftermat Yeah, anything about 1639 01:29:42,120 --> 01:29:44,400 Speaker 1: the crisis. I always disagree with something, and I'm sure 1640 01:29:44,439 --> 01:29:46,760 Speaker 1: you would too, but that's but I'd like to see 1641 01:29:46,800 --> 01:29:49,880 Speaker 1: other people's perspective. Did you really enjoy this? Because this 1642 01:29:50,000 --> 01:29:53,800 Speaker 1: book has been sitting on a shelf, untouched, unloved, not 1643 01:29:54,040 --> 01:29:56,760 Speaker 1: even I have. I didn't. I didn't read all of it, 1644 01:29:56,800 --> 01:29:59,439 Speaker 1: but I read several chapters and not not even in 1645 01:29:59,600 --> 01:30:02,200 Speaker 1: my It's like, do I really Although I will say 1646 01:30:02,880 --> 01:30:07,120 Speaker 1: I've I've really enjoyed his blog. Yeah, and I like 1647 01:30:07,320 --> 01:30:10,840 Speaker 1: the post the I like the post crisis per Nanke 1648 01:30:11,800 --> 01:30:14,000 Speaker 1: better than the pre crisis. He was too blase and 1649 01:30:14,080 --> 01:30:17,760 Speaker 1: too willing to you know, rubber Stamwood Greenspan was doing 1650 01:30:17,840 --> 01:30:20,320 Speaker 1: pre crisis, but in the midst of the crisis and 1651 01:30:20,920 --> 01:30:24,080 Speaker 1: after couldn't have had a better guy there when he 1652 01:30:24,120 --> 01:30:27,040 Speaker 1: stepped up. We were very fortunately, yes, And I was 1653 01:30:27,120 --> 01:30:31,439 Speaker 1: a big critic prior and in hindsight during the crisis. 1654 01:30:32,080 --> 01:30:33,680 Speaker 1: Really you want a guy who's a student of the 1655 01:30:33,720 --> 01:30:39,519 Speaker 1: Great Depression. He was slow to react to what was happening. 1656 01:30:40,000 --> 01:30:42,000 Speaker 1: But then once I think one day he woke up 1657 01:30:42,040 --> 01:30:45,200 Speaker 1: and said, holy count, you know, and and this everything 1658 01:30:45,200 --> 01:30:47,240 Speaker 1: I've studied all my life, it's happening right now as 1659 01:30:47,280 --> 01:30:50,400 Speaker 1: I'm sitting here. You know. It's it's really quite amazing. Yeah. 1660 01:30:50,479 --> 01:30:52,680 Speaker 1: So you know, we we remember when he first got 1661 01:30:52,720 --> 01:30:56,120 Speaker 1: appointed by George W. Bush and I thought, oh, three 1662 01:30:56,280 --> 01:30:59,639 Speaker 1: something like that. He must have not not as chairman, 1663 01:30:59,720 --> 01:31:02,040 Speaker 1: but just on the board. He was ce a counseled 1664 01:31:02,080 --> 01:31:04,960 Speaker 1: Economic Advice Yeah, and that, you know, and that him 1665 01:31:05,040 --> 01:31:07,160 Speaker 1: up to go on the FED. Yeah and that. And 1666 01:31:07,960 --> 01:31:09,479 Speaker 1: I felt sorry for him when he was the c 1667 01:31:09,680 --> 01:31:12,040 Speaker 1: A because he was saying things that really didn't make 1668 01:31:12,120 --> 01:31:15,080 Speaker 1: sense in my view, and I thought, oh man, he there, 1669 01:31:15,200 --> 01:31:17,760 Speaker 1: he's got to be political a little bit, right, And 1670 01:31:18,080 --> 01:31:20,120 Speaker 1: but when once he got but I'm still really happy 1671 01:31:20,160 --> 01:31:22,599 Speaker 1: that he got appointed because you could have got anybody, 1672 01:31:23,400 --> 01:31:25,840 Speaker 1: and uh, we could have got somebody really bad who 1673 01:31:25,920 --> 01:31:29,280 Speaker 1: felt like the FED shouldn't do anything right. And and 1674 01:31:29,880 --> 01:31:32,519 Speaker 1: there are lots of people who think, just let it 1675 01:31:32,680 --> 01:31:35,920 Speaker 1: run its course. It'll be really painful, but then we'll 1676 01:31:35,960 --> 01:31:38,920 Speaker 1: come out the other end, cleansed and better. Well, you know, 1677 01:31:39,000 --> 01:31:42,240 Speaker 1: and I you know, you kind of understand that except 1678 01:31:42,280 --> 01:31:44,760 Speaker 1: for the realistic, it's not realistic, especially when you look 1679 01:31:44,760 --> 01:31:48,440 Speaker 1: at all the people that are seriously injured during the downturn. 1680 01:31:48,920 --> 01:31:53,479 Speaker 1: And and um, I mean instead of instead of picking 1681 01:31:53,560 --> 01:31:55,800 Speaker 1: at ten percent, the uneployment rate might have piked at 1682 01:31:55,800 --> 01:31:58,160 Speaker 1: twenty or twenty five percent. And then and it's not 1683 01:31:58,160 --> 01:32:00,840 Speaker 1: only those twenty percent to get hurt, it's the next 1684 01:32:00,880 --> 01:32:04,160 Speaker 1: ten or they are pulling way back. They're afraid they're 1685 01:32:04,160 --> 01:32:06,960 Speaker 1: going to lose their jobs to paradox of thrift. Yeah, 1686 01:32:07,000 --> 01:32:08,840 Speaker 1: and and and then and then you get I mean 1687 01:32:08,880 --> 01:32:13,040 Speaker 1: you get you get suicide's divorced. Yeah, I mean you can't. 1688 01:32:13,160 --> 01:32:15,120 Speaker 1: You can't let that go on for five seven years 1689 01:32:15,160 --> 01:32:17,360 Speaker 1: and hope it's going to resolve itself. And besides, I think, 1690 01:32:17,640 --> 01:32:20,360 Speaker 1: you know, Cain's kind of pointed out that you've got 1691 01:32:20,439 --> 01:32:23,200 Speaker 1: a problem and it may never ever resolve with something 1692 01:32:23,640 --> 01:32:25,639 Speaker 1: that but you know, if if the if the FED 1693 01:32:25,760 --> 01:32:27,759 Speaker 1: can step up and you can get some physical policy. 1694 01:32:28,040 --> 01:32:31,400 Speaker 1: Gee whiz, we turned it around from a financial crisis perspective. 1695 01:32:31,439 --> 01:32:33,720 Speaker 1: We turned this around better than just about anybody. Ever, 1696 01:32:34,439 --> 01:32:37,080 Speaker 1: the rest of the world certainly is still lagging behind 1697 01:32:37,120 --> 01:32:39,920 Speaker 1: the US. All right, last two questions before they throw 1698 01:32:40,000 --> 01:32:42,280 Speaker 1: us out of the studio. We've been here for almost 1699 01:32:42,320 --> 01:32:45,439 Speaker 1: two hours. So a millennial or a recent college grad 1700 01:32:45,560 --> 01:32:50,040 Speaker 1: comes up to you and says, I'm interested in blogging 1701 01:32:50,400 --> 01:32:54,040 Speaker 1: real estate, um writing, What sort of advice would you 1702 01:32:54,120 --> 01:32:59,200 Speaker 1: give them? Go ahead, have fun? You know. Look, people 1703 01:32:59,240 --> 01:33:01,479 Speaker 1: ask me how I built my traffic. I could ask 1704 01:33:01,520 --> 01:33:05,080 Speaker 1: you how you built your traffic in relentlessly through ten 1705 01:33:05,200 --> 01:33:08,439 Speaker 1: years of brutal work. I just becoming overnight sensation. Yes, 1706 01:33:08,520 --> 01:33:10,400 Speaker 1: I just wrote and wrote and wrote and and people 1707 01:33:10,439 --> 01:33:12,880 Speaker 1: started picking up. People liked what I wrote, picked it up, 1708 01:33:13,000 --> 01:33:16,720 Speaker 1: spread it around, you know, post go viral and and uh, 1709 01:33:17,080 --> 01:33:19,680 Speaker 1: you know, so I don't people ask me, well, how 1710 01:33:19,720 --> 01:33:22,320 Speaker 1: did you advertise? Not? I didn't how to spread the word. 1711 01:33:22,320 --> 01:33:26,160 Speaker 1: I didn't um ever send out emails to journalists that hey, 1712 01:33:26,240 --> 01:33:28,040 Speaker 1: this is an interesting piece, you should look at it. 1713 01:33:28,200 --> 01:33:30,360 Speaker 1: Never so I've never I've never advertised it at all. 1714 01:33:30,840 --> 01:33:34,000 Speaker 1: So I mean, I guess I'm advertising it now. But yeah, 1715 01:33:34,040 --> 01:33:37,080 Speaker 1: but you're talking about after a decade of putting it out. 1716 01:33:37,200 --> 01:33:40,720 Speaker 1: This this is less advertising than a a victory lap 1717 01:33:40,840 --> 01:33:44,840 Speaker 1: slash retrospective. It's not like look at look at Bill 1718 01:33:44,880 --> 01:33:50,000 Speaker 1: out Um promoting look at him hyping calculated risk. I've 1719 01:33:50,120 --> 01:33:54,519 Speaker 1: asked you full disclosure. How many times have I said, Hey, 1720 01:33:54,640 --> 01:33:57,519 Speaker 1: let's let's get you, let's do something, let's talk about this. 1721 01:33:58,320 --> 01:34:02,320 Speaker 1: I recall linking to you back in I don't know, 1722 01:34:03,120 --> 01:34:06,760 Speaker 1: oh five oh six I was doing. That's probably where 1723 01:34:06,800 --> 01:34:09,400 Speaker 1: my traffic came from. I was first I was doing 1724 01:34:09,479 --> 01:34:11,680 Speaker 1: the link fest for the street dot com, and then 1725 01:34:11,720 --> 01:34:14,160 Speaker 1: I was doing them on the Big Picture and I 1726 01:34:14,280 --> 01:34:18,360 Speaker 1: recall and you sent like a really lovely email. I 1727 01:34:18,520 --> 01:34:21,000 Speaker 1: have it somewhere. Hey, thanks for the link, but you 1728 01:34:21,240 --> 01:34:23,640 Speaker 1: you know, you crashed our site. You took it offline. 1729 01:34:24,040 --> 01:34:26,439 Speaker 1: And it wasn't like I was getting that much traffic. 1730 01:34:26,600 --> 01:34:29,679 Speaker 1: But in the scheme of bloggers, if you were getting 1731 01:34:29,680 --> 01:34:32,160 Speaker 1: a thousand a day, that was a lot, you know, 1732 01:34:32,280 --> 01:34:35,040 Speaker 1: way back in the early days. But so your advice 1733 01:34:35,080 --> 01:34:37,800 Speaker 1: to someone who wants to start today this late date 1734 01:34:38,280 --> 01:34:41,080 Speaker 1: covering housing or you would say, go for it. Yeah, 1735 01:34:41,120 --> 01:34:43,280 Speaker 1: I think I think anybody can I think anybody can 1736 01:34:43,400 --> 01:34:45,400 Speaker 1: do it if I mean, if there if they have 1737 01:34:45,520 --> 01:34:48,560 Speaker 1: something to add there. I mean, you just have to 1738 01:34:48,680 --> 01:34:50,240 Speaker 1: work at it and be and put up with a 1739 01:34:50,320 --> 01:34:54,120 Speaker 1: low traffic to start. And you know, how how how 1740 01:34:54,200 --> 01:34:56,639 Speaker 1: do you it's not I wouldn't consider a money maker. 1741 01:34:56,720 --> 01:34:58,519 Speaker 1: I mean if it's if it's somebody's career, but if 1742 01:34:58,520 --> 01:35:02,000 Speaker 1: it's somebody's sidelight, uh, something they do because they're passionate 1743 01:35:02,000 --> 01:35:04,559 Speaker 1: about their passion about it and they've got something another 1744 01:35:04,680 --> 01:35:07,720 Speaker 1: real job, which is what really most bloggers do. What's 1745 01:35:07,800 --> 01:35:09,600 Speaker 1: up with you and zero heads? You've you've written some 1746 01:35:09,800 --> 01:35:13,600 Speaker 1: some critical things. He's not happy with me. Oh I 1747 01:35:14,000 --> 01:35:16,400 Speaker 1: I you know, I have no relationship with him at all. 1748 01:35:16,439 --> 01:35:19,840 Speaker 1: I just think the sits a joke. Really, yeah, because 1749 01:35:20,240 --> 01:35:23,640 Speaker 1: every now and then there's something of interest because he 1750 01:35:23,720 --> 01:35:26,680 Speaker 1: has an expertise and derivatives what have you. But how 1751 01:35:26,760 --> 01:35:27,960 Speaker 1: do you how do you know? How do you can't 1752 01:35:28,000 --> 01:35:31,880 Speaker 1: find it's you know, I only have so much time 1753 01:35:31,960 --> 01:35:33,880 Speaker 1: every day. I think this is a good lesson for 1754 01:35:34,000 --> 01:35:36,400 Speaker 1: everybody is you have to you have to learn the 1755 01:35:36,479 --> 01:35:40,320 Speaker 1: sites or the newspaper journalists that you want to read, 1756 01:35:40,920 --> 01:35:42,720 Speaker 1: and and every once in a while you branch out 1757 01:35:42,760 --> 01:35:45,639 Speaker 1: and pick up other people and and then decide whether 1758 01:35:45,680 --> 01:35:47,080 Speaker 1: you want to keep reading them. You know, if I 1759 01:35:47,120 --> 01:35:51,400 Speaker 1: see John Hills and Wrath at the Nick Tamaris, I 1760 01:35:51,439 --> 01:35:53,680 Speaker 1: love both the work at the Walston Journal, I read 1761 01:35:53,720 --> 01:35:56,120 Speaker 1: the article. It's just automatic, you know. I read everything 1762 01:35:56,120 --> 01:35:59,439 Speaker 1: by Paul Krugman, and I read you know, um, I 1763 01:35:59,640 --> 01:36:01,800 Speaker 1: have my group of people that I always read, and 1764 01:36:01,880 --> 01:36:04,439 Speaker 1: I branch out and read other people too, and then 1765 01:36:04,600 --> 01:36:07,120 Speaker 1: and sometimes they fall into that group, and and then 1766 01:36:07,160 --> 01:36:09,280 Speaker 1: I'll start reading them if I see their name. Oh yeah, 1767 01:36:09,680 --> 01:36:11,800 Speaker 1: I gotta. I think everybody has to have that filter. 1768 01:36:12,040 --> 01:36:14,040 Speaker 1: I can't waste my time going through a hundred posts 1769 01:36:14,080 --> 01:36:18,080 Speaker 1: to find the one little nute um and and you know, uh, 1770 01:36:18,680 --> 01:36:21,240 Speaker 1: way back when I don't. I don't think I've been 1771 01:36:21,280 --> 01:36:24,680 Speaker 1: to zero hedge site in five years. Really, Yeah, that's fascinating. 1772 01:36:24,760 --> 01:36:27,280 Speaker 1: I have friends who are always sending me stuff, and 1773 01:36:27,479 --> 01:36:30,799 Speaker 1: one out of five things are are kind of interesting them. 1774 01:36:31,479 --> 01:36:32,840 Speaker 1: I know a lot of people read it. I don't 1775 01:36:32,880 --> 01:36:35,320 Speaker 1: know why. And you know what, maybe they're better today, 1776 01:36:35,439 --> 01:36:37,880 Speaker 1: you know, maybe maybe I maybe I've been I've been 1777 01:36:37,920 --> 01:36:41,400 Speaker 1: blaming zero Hedge. I've been blaming that site for hedge 1778 01:36:41,439 --> 01:36:44,120 Speaker 1: fund under performance for the past five years. They've been 1779 01:36:44,160 --> 01:36:46,920 Speaker 1: relentlessly negative. They missed a giant move in equity, but 1780 01:36:47,000 --> 01:36:49,600 Speaker 1: they were they were saying short uh in March of 1781 01:36:49,680 --> 01:36:52,120 Speaker 1: two thousand nine when the market would hit six six six, 1782 01:36:52,360 --> 01:36:54,840 Speaker 1: good time and uh. And they've never changed as far 1783 01:36:54,880 --> 01:36:56,760 Speaker 1: as for you know, I was I used to go 1784 01:36:56,920 --> 01:36:59,439 Speaker 1: for entertainment purpose, well you know back when, back when 1785 01:36:59,439 --> 01:37:01,760 Speaker 1: I first did and and I'm sure this is true 1786 01:37:01,760 --> 01:37:04,400 Speaker 1: for you too, is that. Um there was kind of 1787 01:37:04,560 --> 01:37:09,280 Speaker 1: like camaraderie among the blogs. Absolutely. If I saw something 1788 01:37:09,400 --> 01:37:11,800 Speaker 1: wrong or on on another side, or they saw something 1789 01:37:11,880 --> 01:37:15,240 Speaker 1: wrong on mine, I we would exchange emails. Yeah, yeah, hey, 1790 01:37:15,280 --> 01:37:16,720 Speaker 1: I think that maybe you're looking at this. And it 1791 01:37:16,880 --> 01:37:19,280 Speaker 1: was great because then I could correct my article. Um 1792 01:37:19,800 --> 01:37:23,280 Speaker 1: I zero Hedge came along. You know, they didn't call 1793 01:37:23,360 --> 01:37:25,960 Speaker 1: the recession at all, obviously, didn't call it recovery. They 1794 01:37:25,960 --> 01:37:28,080 Speaker 1: didn't see the housing bubble then, none of that because 1795 01:37:28,080 --> 01:37:30,680 Speaker 1: they yeah, they came out way after and it was 1796 01:37:30,760 --> 01:37:34,960 Speaker 1: all gloom and doom, yellow journalism. But like somebody sent 1797 01:37:35,040 --> 01:37:36,600 Speaker 1: me an article from it and I said, oh, a 1798 01:37:36,640 --> 01:37:38,599 Speaker 1: new site, you know, and I read it and I said, 1799 01:37:38,640 --> 01:37:42,080 Speaker 1: well you I sent the guy an email and uh, 1800 01:37:42,320 --> 01:37:45,439 Speaker 1: and I got the rudest reply and I went, I went, 1801 01:37:45,560 --> 01:37:47,960 Speaker 1: what the hell I here? I am reaching out. I'm 1802 01:37:47,960 --> 01:37:49,680 Speaker 1: not I'm not publishing it on my side. I'm not 1803 01:37:49,800 --> 01:37:54,800 Speaker 1: embarrassing these guys. They just just just you can't you 1804 01:37:54,840 --> 01:37:56,680 Speaker 1: really can't look at the data this way. You need 1805 01:37:56,760 --> 01:37:58,760 Speaker 1: to do this. And it's something I knew really well, 1806 01:37:59,400 --> 01:38:02,439 Speaker 1: and and you know, screw you kind of response and 1807 01:38:02,600 --> 01:38:05,240 Speaker 1: and okay, fine, you know, you know, I had a 1808 01:38:05,439 --> 01:38:07,720 Speaker 1: lunch with Chris Whalen set up a lunch with him 1809 01:38:07,760 --> 01:38:09,720 Speaker 1: and me and a bunch of other people because I 1810 01:38:09,880 --> 01:38:12,320 Speaker 1: was interested in the derivative stuff he was writing about 1811 01:38:12,400 --> 01:38:15,320 Speaker 1: was excellent, and the high freagency trading stuff. He had 1812 01:38:15,360 --> 01:38:20,240 Speaker 1: some really good insights. And then everything all kinda went 1813 01:38:20,360 --> 01:38:24,040 Speaker 1: to just a degree of negativity and well being. Well 1814 01:38:24,080 --> 01:38:27,360 Speaker 1: being negative drives traffic for a lot of people. I 1815 01:38:27,479 --> 01:38:29,880 Speaker 1: guess you know, you if you if you're constantly bearish. 1816 01:38:30,000 --> 01:38:32,360 Speaker 1: I always say that blogs having in centator to be 1817 01:38:32,400 --> 01:38:34,760 Speaker 1: bearish because it drives traffic. It's kind of like, you know, 1818 01:38:34,840 --> 01:38:37,720 Speaker 1: Wall Street Dalis having in centator to be bullish, you know, 1819 01:38:38,160 --> 01:38:42,000 Speaker 1: and and it's the rare great economist on Wall Street 1820 01:38:42,040 --> 01:38:45,479 Speaker 1: who can say we've got a problem. Um, and it's 1821 01:38:45,720 --> 01:38:48,320 Speaker 1: it's you know, the very few bloggers are willing to 1822 01:38:48,439 --> 01:38:51,760 Speaker 1: go both ways. So let's let me ask you my 1823 01:38:51,960 --> 01:38:55,880 Speaker 1: very last question, my favorite question, and that is, what 1824 01:38:56,120 --> 01:38:59,600 Speaker 1: is it that you know about real estate, about mortgages, 1825 01:39:00,040 --> 01:39:03,519 Speaker 1: out writing and blogging that you wish you knew back 1826 01:39:03,600 --> 01:39:06,200 Speaker 1: in two thousand and five when you launched the site? Well, 1827 01:39:06,240 --> 01:39:08,840 Speaker 1: I wish I had met Tanta two years earlier. As 1828 01:39:08,880 --> 01:39:12,320 Speaker 1: far as mortgages, Uh, everything I know I learned from her. 1829 01:39:12,560 --> 01:39:16,160 Speaker 1: So uh as far as real estate, you know, I 1830 01:39:17,000 --> 01:39:19,759 Speaker 1: it was it was so much fun early on reading 1831 01:39:19,840 --> 01:39:22,439 Speaker 1: through all the technical documents and all of the sites 1832 01:39:22,520 --> 01:39:25,120 Speaker 1: that would provide that as to how they gathered their data, 1833 01:39:25,640 --> 01:39:28,680 Speaker 1: and so I really learned a lot. Um. If I'd 1834 01:39:28,720 --> 01:39:30,360 Speaker 1: known that a little earlier, maybe I could have put 1835 01:39:30,400 --> 01:39:33,040 Speaker 1: all the pieces together just a little bit earlier. Um, 1836 01:39:34,240 --> 01:39:36,800 Speaker 1: you know, I I it was. It was a weird 1837 01:39:37,120 --> 01:39:39,479 Speaker 1: thing in two thousand five. To me, I could clearly 1838 01:39:39,560 --> 01:39:42,519 Speaker 1: see that the market was overvalued, that there was really 1839 01:39:42,560 --> 01:39:46,479 Speaker 1: bad mortgages. But I kept asking myself, well, why why 1840 01:39:46,600 --> 01:39:48,640 Speaker 1: are they making these mortgages to people that are never 1841 01:39:48,680 --> 01:39:51,120 Speaker 1: going to pay them? I personally would never learn money 1842 01:39:51,120 --> 01:39:53,000 Speaker 1: to people that aren't going to pay me, you know. 1843 01:39:53,120 --> 01:39:54,800 Speaker 1: I it took me a two or three years to 1844 01:39:54,840 --> 01:39:58,479 Speaker 1: finally really understand how they were rating based on two 1845 01:39:58,880 --> 01:40:03,400 Speaker 1: nine nineties methodology. The methodology had changed. How that how 1846 01:40:03,600 --> 01:40:07,519 Speaker 1: you know that you had this real uh originate to 1847 01:40:07,800 --> 01:40:10,840 Speaker 1: to distribute model that that was just pulling. You know, 1848 01:40:10,880 --> 01:40:12,800 Speaker 1: people were investing in these things that they thought were 1849 01:40:12,840 --> 01:40:15,640 Speaker 1: triple A and they paid a higher yield than other 1850 01:40:15,680 --> 01:40:17,760 Speaker 1: triple as, which wish you can sell that you can 1851 01:40:17,800 --> 01:40:20,080 Speaker 1: sell an infinite amount of that because people can can 1852 01:40:20,240 --> 01:40:22,960 Speaker 1: arbitrage between the triple as. You know, I mean it's 1853 01:40:23,000 --> 01:40:25,519 Speaker 1: crazy how that whole worked. Once you realize how that 1854 01:40:25,560 --> 01:40:28,080 Speaker 1: whole mechanism worked, and then it was obvious how it happened. 1855 01:40:28,680 --> 01:40:31,200 Speaker 1: You know, I just couldn't understand originally why they make 1856 01:40:31,280 --> 01:40:34,120 Speaker 1: loans that were never gonna get paid. Well, if you 1857 01:40:34,200 --> 01:40:36,679 Speaker 1: can my my favorite. I did a ton of research 1858 01:40:36,760 --> 01:40:40,720 Speaker 1: for Bailout Nation. One of my favorite little research discoveries 1859 01:40:41,240 --> 01:40:47,080 Speaker 1: were that the primarily located in California, private sector mortgage 1860 01:40:47,240 --> 01:40:49,920 Speaker 1: lenders who would then sell it to Wall Street would 1861 01:40:49,960 --> 01:40:52,719 Speaker 1: sell it to Wall Street with a nine day warranty. 1862 01:40:53,320 --> 01:40:57,040 Speaker 1: They would guarantee that this mortgage won't default, This thirty 1863 01:40:57,080 --> 01:41:00,920 Speaker 1: year mortgage won't default for three months. Now, stop and 1864 01:41:00,960 --> 01:41:05,600 Speaker 1: think about how misaligned those incentives are. I have a 1865 01:41:05,720 --> 01:41:07,800 Speaker 1: question for you that's not on my list. I have 1866 01:41:07,960 --> 01:41:10,120 Speaker 1: to ask, because I've been thinking about it. Are we 1867 01:41:10,200 --> 01:41:12,479 Speaker 1: ever going to see a calculated risk book from you? 1868 01:41:13,760 --> 01:41:16,360 Speaker 1: I don't think so, really, because I think that could 1869 01:41:16,400 --> 01:41:18,920 Speaker 1: be really interesting. It looks like a lot of work 1870 01:41:18,960 --> 01:41:21,160 Speaker 1: to me. Yet it's a lot of work. But when 1871 01:41:21,200 --> 01:41:23,960 Speaker 1: you're done, I have a pH d. That's what it 1872 01:41:24,000 --> 01:41:26,840 Speaker 1: feels like. Okay, Well, I think people would buy the 1873 01:41:26,920 --> 01:41:29,320 Speaker 1: Calculators book, and I think it could be. That's very 1874 01:41:29,360 --> 01:41:31,920 Speaker 1: nice to you to say, so you don't you know 1875 01:41:32,040 --> 01:41:34,240 Speaker 1: how much work goes into it. I know. Hey, listen, 1876 01:41:34,280 --> 01:41:37,840 Speaker 1: it's been five years and I've been thinking about, well, 1877 01:41:38,080 --> 01:41:40,519 Speaker 1: I'm just now five years later on my Alright, maybe 1878 01:41:40,560 --> 01:41:42,840 Speaker 1: I'll start thinking about, well you could you could see 1879 01:41:42,880 --> 01:41:45,160 Speaker 1: five years. I'm sorry it's seven years later, but you know, 1880 01:41:45,520 --> 01:41:47,960 Speaker 1: your master's in business, You've You've had over a hundred 1881 01:41:48,000 --> 01:41:51,320 Speaker 1: interviews on my list. That's I've had two different publishers 1882 01:41:51,400 --> 01:41:53,840 Speaker 1: reach out. Three different publishers reached out to me. Hey, 1883 01:41:53,880 --> 01:41:55,800 Speaker 1: would you like to do this as a book? Sure? 1884 01:41:56,360 --> 01:41:57,880 Speaker 1: I think it would be a great book. It could 1885 01:41:57,920 --> 01:42:01,640 Speaker 1: be fun. Bill. Thank you much for for doing this. 1886 01:42:01,960 --> 01:42:05,040 Speaker 1: This has just been really fascinating for for those of 1887 01:42:05,120 --> 01:42:08,760 Speaker 1: you who listened, I apologize for babbling. I know Bill 1888 01:42:08,880 --> 01:42:11,960 Speaker 1: for so long, and literally it's the first time we've 1889 01:42:12,000 --> 01:42:16,479 Speaker 1: actually sat down and chatted. I was very chatty, and 1890 01:42:16,640 --> 01:42:20,360 Speaker 1: it's because when you know someone virtually for twelve years 1891 01:42:20,400 --> 01:42:22,400 Speaker 1: and you finally get to sit down and talk, you 1892 01:42:22,520 --> 01:42:25,200 Speaker 1: feel compelled to uh, to hold up your half of 1893 01:42:25,200 --> 01:42:29,240 Speaker 1: the conversation. For those of you who have enjoyed this conversation, 1894 01:42:29,840 --> 01:42:31,479 Speaker 1: be sure to look up an inch or down an 1895 01:42:31,520 --> 01:42:33,519 Speaker 1: inch on Apple iTunes and you can see any of 1896 01:42:33,560 --> 01:42:37,360 Speaker 1: the other hundred plus conversations we've had, which is in 1897 01:42:37,439 --> 01:42:41,400 Speaker 1: itself a mind blowing data point. I would be remiss 1898 01:42:41,520 --> 01:42:46,040 Speaker 1: if I did not thank my producer and Today's recording engineer, 1899 01:42:46,560 --> 01:42:50,559 Speaker 1: Charlie Volmer, our booker Taylor Riggs, and Mike Batnick, who 1900 01:42:50,640 --> 01:42:55,080 Speaker 1: is the head of research. We love your comments, feedbacks, criticisms, 1901 01:42:55,160 --> 01:42:59,000 Speaker 1: and and other assorted responses. Be sure and right to 1902 01:42:59,160 --> 01:43:04,439 Speaker 1: us at M I B Podcasts at Bloomberg dot net. 1903 01:43:05,160 --> 01:43:08,559 Speaker 1: I'm Barry Ritolts. You've been listening to Masters in Business 1904 01:43:08,960 --> 01:43:10,080 Speaker 1: on Bloomberg Radio