1 00:00:02,120 --> 00:00:06,040 Speaker 1: This is Master's in Business with Barry rid Holds on 2 00:00:06,280 --> 00:00:08,320 Speaker 1: Bloomberg Radio. 3 00:00:09,080 --> 00:00:13,160 Speaker 2: This week on the podcast what a Delight, I got 4 00:00:13,160 --> 00:00:17,639 Speaker 2: to spend about two hours with Sir Angus Deeton. He 5 00:00:17,680 --> 00:00:20,480 Speaker 2: won the Nobel Prize in twenty fifteen for his work 6 00:00:20,880 --> 00:00:26,800 Speaker 2: on consumption, poverty, welfare, wealth and health inequality. Really, the 7 00:00:26,840 --> 00:00:32,120 Speaker 2: work he's done on inequality tame after the Nobel Prize, 8 00:00:32,440 --> 00:00:34,159 Speaker 2: based on a book him and his wife put out 9 00:00:34,200 --> 00:00:37,680 Speaker 2: in a number of papers, he wrote, what can I say? 10 00:00:38,440 --> 00:00:43,480 Speaker 2: He is just so fascinating, such an interesting person born 11 00:00:43,520 --> 00:00:46,239 Speaker 2: in the UK, grows up in Scotland, is becomes a 12 00:00:46,280 --> 00:00:50,480 Speaker 2: professor in the UK and then says, let's go check 13 00:00:50,479 --> 00:00:54,280 Speaker 2: out that place America and starts teaching at Princeton forty 14 00:00:54,360 --> 00:00:58,680 Speaker 2: years ago. He's been here about half his life. I 15 00:00:58,800 --> 00:01:02,760 Speaker 2: found this conversation be just delightful, so interesting, so fascinating. 16 00:01:03,160 --> 00:01:10,160 Speaker 2: He is so knowledgeable about so many unusual areas in economics. 17 00:01:10,400 --> 00:01:14,640 Speaker 2: We only got to scratch the surface on some of them. Healthcare, 18 00:01:14,880 --> 00:01:21,319 Speaker 2: minimum wage, what really makes people happy? And how significant 19 00:01:21,680 --> 00:01:26,240 Speaker 2: having or not having a college degree. You know, the 20 00:01:26,360 --> 00:01:30,840 Speaker 2: United States has very much become a bifurcated nation and 21 00:01:30,880 --> 00:01:36,760 Speaker 2: where Professor Daton draws the line, if you don't have 22 00:01:37,000 --> 00:01:41,200 Speaker 2: a college degree, you are just at a huge disadvantage 23 00:01:41,360 --> 00:01:44,240 Speaker 2: in this society, and he brings the receipts, he has 24 00:01:44,280 --> 00:01:47,760 Speaker 2: all the data that proves it. I found this just 25 00:01:47,800 --> 00:01:52,080 Speaker 2: to be fascinating, charming, delightful, and I think you will also, 26 00:01:52,920 --> 00:01:57,480 Speaker 2: with no further ado my conversation with Sir Angus Deeton. 27 00:01:58,120 --> 00:01:59,480 Speaker 1: Thank you very much for having me. 28 00:01:59,680 --> 00:02:03,720 Speaker 2: Well, well, I've left out about ninety percent of your CV. 29 00:02:04,360 --> 00:02:08,000 Speaker 2: You're the author of two hundred plus papers, six books. 30 00:02:09,120 --> 00:02:12,840 Speaker 2: Deaths of Despair, which you wrote with and Case Happens 31 00:02:12,880 --> 00:02:15,640 Speaker 2: to Be Your Wife was a New York Times bestseller, 32 00:02:16,040 --> 00:02:20,680 Speaker 2: and your latest book, Economics in America An Immigrant Economist, 33 00:02:21,120 --> 00:02:24,520 Speaker 2: explores the land of inequality. We're going to talk about 34 00:02:24,520 --> 00:02:28,440 Speaker 2: in a few minutes, but let's just start with what 35 00:02:28,520 --> 00:02:34,120 Speaker 2: you cover, which is kind of fascinating health, happiness, development, poverty, 36 00:02:34,160 --> 00:02:38,080 Speaker 2: well being, inequality, and the best ways to collect and 37 00:02:38,160 --> 00:02:42,519 Speaker 2: interpret evidence for a public policy. That is quite an eclectic, 38 00:02:43,240 --> 00:02:46,560 Speaker 2: broad set of interests. How do they all relate to 39 00:02:46,600 --> 00:02:47,040 Speaker 2: each other? 40 00:02:47,240 --> 00:02:50,240 Speaker 1: Well, I think there are all sort of sides of 41 00:02:50,280 --> 00:02:55,080 Speaker 1: the same thing, which is, I'm interested in what makes 42 00:02:55,120 --> 00:02:58,200 Speaker 1: people tick. You know what makes people do what they do. 43 00:02:58,680 --> 00:03:02,000 Speaker 1: I'm interested in their wealth being in a fairly broad sense. 44 00:03:02,160 --> 00:03:04,000 Speaker 1: I mean, in England we used to call it welfare, 45 00:03:04,040 --> 00:03:05,600 Speaker 1: but welfare here means something else. 46 00:03:05,639 --> 00:03:07,840 Speaker 2: You got a dirty connotation in the United States. 47 00:03:07,960 --> 00:03:11,160 Speaker 1: I'm interested in people's wellbeing, and that's to do with 48 00:03:11,200 --> 00:03:14,120 Speaker 1: how much they spend, how much they save. You know, 49 00:03:14,240 --> 00:03:16,960 Speaker 1: it's to do with getting from poor country, turning poor 50 00:03:17,000 --> 00:03:20,480 Speaker 1: countries into rich countries. It's to do with poverty, is 51 00:03:20,480 --> 00:03:22,840 Speaker 1: to do with inequality. All of these things hang together. 52 00:03:22,919 --> 00:03:25,760 Speaker 1: And I'm a data guy, so I'm really interested in 53 00:03:25,840 --> 00:03:27,160 Speaker 1: how you interpret data. 54 00:03:27,240 --> 00:03:30,639 Speaker 2: Let's just start with your career, which I love how 55 00:03:30,680 --> 00:03:33,880 Speaker 2: you describe your early part of your career. After a 56 00:03:34,040 --> 00:03:38,120 Speaker 2: brief and undistinguished career at the Bank of England, you 57 00:03:38,240 --> 00:03:42,640 Speaker 2: return to academia as a professor of econometrics at the 58 00:03:42,760 --> 00:03:46,600 Speaker 2: University of Bristol. Brief and undistinguished. Who puts that in 59 00:03:46,600 --> 00:03:47,080 Speaker 2: their CV? 60 00:03:48,120 --> 00:03:50,080 Speaker 1: Well, I was not cut out to be a banker. 61 00:03:50,160 --> 00:03:52,480 Speaker 1: But one of the things that was good about spending 62 00:03:52,560 --> 00:03:55,600 Speaker 1: nine months there was I discovered that I wasn't cut 63 00:03:55,640 --> 00:03:58,600 Speaker 1: out to be a banker and it was much more 64 00:03:58,680 --> 00:04:01,600 Speaker 1: fun to be an academic. There's also I had a 65 00:04:01,640 --> 00:04:03,520 Speaker 1: girlfriend in Cambridge. 66 00:04:03,520 --> 00:04:06,720 Speaker 2: So about that. One of the things I found fascinating 67 00:04:07,000 --> 00:04:10,360 Speaker 2: in your Nopell Prize acceptance speech, for lack of a 68 00:04:10,360 --> 00:04:14,440 Speaker 2: better word, you said you became an economist by accident. 69 00:04:14,840 --> 00:04:16,440 Speaker 2: You're going to have to give us some more color 70 00:04:16,480 --> 00:04:17,719 Speaker 2: on that. Well. 71 00:04:17,800 --> 00:04:20,240 Speaker 1: I was always interested in a wide range of things. 72 00:04:20,279 --> 00:04:23,640 Speaker 1: So when I was at this very fancy private school 73 00:04:23,680 --> 00:04:26,200 Speaker 1: that I was at as a kid, I did math 74 00:04:26,240 --> 00:04:28,040 Speaker 1: because it gave me a huge amount of free time 75 00:04:28,120 --> 00:04:30,560 Speaker 1: to do the things I really cared about, like reading 76 00:04:30,600 --> 00:04:33,880 Speaker 1: books and playing the pipe organ and playing rugby and 77 00:04:33,960 --> 00:04:37,200 Speaker 1: sports and things. But when I got to Cambridge, you know, 78 00:04:37,279 --> 00:04:40,120 Speaker 1: the math was sort of serious there, and so I 79 00:04:40,160 --> 00:04:44,279 Speaker 1: discovered this was not really for me. And like most students, 80 00:04:44,279 --> 00:04:46,280 Speaker 1: you move up a grade and you discover you've been 81 00:04:46,320 --> 00:04:48,920 Speaker 1: the smartest thing there's ever been until you get there 82 00:04:48,960 --> 00:04:50,680 Speaker 1: and all of a sudden, there's a whole lot of 83 00:04:50,720 --> 00:04:51,360 Speaker 1: other people. 84 00:04:51,120 --> 00:04:53,000 Speaker 2: Who are These guys are really good at this. 85 00:04:53,080 --> 00:04:55,840 Speaker 1: They're really good at this. So after a couple of years, 86 00:04:56,160 --> 00:04:59,560 Speaker 1: in something of despair, my tutors said to me, you 87 00:04:59,560 --> 00:05:02,760 Speaker 1: have to give up doing this, And I said, well, 88 00:05:03,080 --> 00:05:04,479 Speaker 1: you know what, could I do. They said, well, you 89 00:05:04,480 --> 00:05:08,080 Speaker 1: could leave, and I said, without a degree, my dad 90 00:05:08,120 --> 00:05:10,840 Speaker 1: would be very unhappy. So I said, what's the alternaty said, 91 00:05:10,839 --> 00:05:12,839 Speaker 1: There's only one other thing for people like you. 92 00:05:12,960 --> 00:05:16,560 Speaker 2: It's called economics, right, Economics for people who were only 93 00:05:16,640 --> 00:05:18,360 Speaker 2: fair at mathematics or. 94 00:05:18,320 --> 00:05:20,960 Speaker 1: Something like that. I wasn't a bad mathematician, and I've 95 00:05:21,040 --> 00:05:24,040 Speaker 1: used a lot of math in my career as an economist, 96 00:05:24,120 --> 00:05:26,400 Speaker 1: and it's a very useful thing. But I just had 97 00:05:26,480 --> 00:05:28,839 Speaker 1: lost interest in it anymore. And as soon as I 98 00:05:28,920 --> 00:05:31,120 Speaker 1: started studying economics, I always thought it hooked. 99 00:05:31,279 --> 00:05:35,719 Speaker 2: That raises a question. You're a lad from Edinburgh, how 100 00:05:35,720 --> 00:05:39,440 Speaker 2: do you become so interested in United States economics? It 101 00:05:39,440 --> 00:05:42,640 Speaker 2: would seem that there's a ton of history and a 102 00:05:42,720 --> 00:05:46,200 Speaker 2: lot of stuff happening in the UK. What brought you here? 103 00:05:46,880 --> 00:05:50,120 Speaker 1: Well, I think I'd remember I was an academic economist, 104 00:05:50,480 --> 00:05:54,680 Speaker 1: and it was pretty clear from the very first economics 105 00:05:54,720 --> 00:05:58,880 Speaker 1: book I read, which was by Paul Samuelson, that the 106 00:05:58,880 --> 00:06:02,480 Speaker 1: most famous, most interesting economists were working in the US. 107 00:06:02,760 --> 00:06:04,919 Speaker 1: I mean, it was a bigger country. That had not 108 00:06:05,080 --> 00:06:08,800 Speaker 1: been true forty years before when Keynes was in Cambridge, right, 109 00:06:08,800 --> 00:06:11,839 Speaker 1: and so on. But you know, the Kynesianism had sort 110 00:06:11,839 --> 00:06:15,160 Speaker 1: of lost its well, he was no longer alive, right, 111 00:06:15,360 --> 00:06:19,760 Speaker 1: and the old Kynsians were a bit grumpy and not 112 00:06:19,960 --> 00:06:21,000 Speaker 1: so very interesting. 113 00:06:21,160 --> 00:06:24,480 Speaker 2: At the time. You have Paul Samuelson at MIT, you 114 00:06:24,560 --> 00:06:28,680 Speaker 2: have Milton Friedman at Chicago. You have a run of people. 115 00:06:29,160 --> 00:06:32,200 Speaker 2: Maybe it's a little early for the Berkeley crowd and 116 00:06:32,320 --> 00:06:34,880 Speaker 2: Princeton Harvard Yale crowd comes a little later. 117 00:06:35,440 --> 00:06:37,359 Speaker 1: There were a lot of people I remember reading the 118 00:06:37,400 --> 00:06:40,719 Speaker 1: Princeton Studies and International Finance, which seemed to me very 119 00:06:40,760 --> 00:06:44,039 Speaker 1: interesting at the time. I'd met Fritz Makhlop, who was 120 00:06:44,080 --> 00:06:47,240 Speaker 1: at Princeton when I was still in Britain. For instance, 121 00:06:48,000 --> 00:06:50,560 Speaker 1: there was Bob Solo, who was always, you know, a 122 00:06:50,600 --> 00:06:53,920 Speaker 1: great hero of mine, even long before I met him. 123 00:06:54,000 --> 00:06:57,039 Speaker 1: I mean, that paper on Economic Growth is a transcendent 124 00:06:57,080 --> 00:07:00,240 Speaker 1: piece of work and really sort of shaped the way 125 00:07:00,760 --> 00:07:04,680 Speaker 1: generations of economists have thought. And it's one of these 126 00:07:04,680 --> 00:07:07,599 Speaker 1: things that really does tell you something that you've always 127 00:07:07,640 --> 00:07:10,280 Speaker 1: thought is really not quite right, and it just comes 128 00:07:10,280 --> 00:07:12,600 Speaker 1: from thinking about it harder. And boy, was that an 129 00:07:12,640 --> 00:07:15,480 Speaker 1: amazing example to all of us. There were also a 130 00:07:15,520 --> 00:07:18,240 Speaker 1: lot of econometricians here, and I was sort of into 131 00:07:18,240 --> 00:07:21,320 Speaker 1: My first job as a professor was a professor of 132 00:07:21,320 --> 00:07:24,400 Speaker 1: econometrics at Bristol, So you know, I took my math 133 00:07:24,440 --> 00:07:26,040 Speaker 1: into statistics and things. 134 00:07:26,880 --> 00:07:30,720 Speaker 2: Am I remembering correctly? Is Solo the economist who said 135 00:07:30,920 --> 00:07:33,720 Speaker 2: productivity is everywhere except the economic data? 136 00:07:33,720 --> 00:07:35,880 Speaker 1: Am I getting one of the many clever things right? 137 00:07:36,200 --> 00:07:39,680 Speaker 2: He was quite an influential economist. So you have all 138 00:07:39,760 --> 00:07:43,600 Speaker 2: of these big economic names in the United States taking 139 00:07:43,640 --> 00:07:47,480 Speaker 2: the mantle from Kines and other people in the UK 140 00:07:47,640 --> 00:07:52,119 Speaker 2: and elsewhere. How do you translate that into a job 141 00:07:52,160 --> 00:07:55,160 Speaker 2: at Princeton when you're working at Cambridge or Bristol. 142 00:07:55,360 --> 00:07:57,840 Speaker 1: Well, I was working at Bristol. I was publishing papers 143 00:07:57,880 --> 00:08:01,760 Speaker 1: that were attracting a certain amount of attention. I'd met 144 00:08:01,800 --> 00:08:04,440 Speaker 1: some of the Princeton people at a conference that i'd 145 00:08:04,560 --> 00:08:08,520 Speaker 1: organized helped organize in Italy. Become very good friends with 146 00:08:08,600 --> 00:08:14,920 Speaker 1: the Orly Ashenfelter, who's another incredibly influential person in modern economics. 147 00:08:15,080 --> 00:08:17,440 Speaker 1: And I went to visit Princeton for a year in 148 00:08:17,560 --> 00:08:21,160 Speaker 1: seventy nine and really liked it. At Bristol at that 149 00:08:21,360 --> 00:08:25,640 Speaker 1: time was suffering from a real cash crunch. Missus Thatcher 150 00:08:25,760 --> 00:08:29,720 Speaker 1: didn't care for the universities very much. Really, yeah, really. 151 00:08:29,480 --> 00:08:32,560 Speaker 2: That's surprising to someone in the United States because the 152 00:08:33,040 --> 00:08:36,440 Speaker 2: especially the elite universities, they always seem to have a 153 00:08:36,480 --> 00:08:39,920 Speaker 2: ton of cash. The joke is Harvard is a fifty 154 00:08:40,000 --> 00:08:43,280 Speaker 2: billion dollar hedge fund with a small liberal arts college 155 00:08:43,280 --> 00:08:46,240 Speaker 2: attached to it. I'm surprised to learn of that. 156 00:08:46,320 --> 00:08:50,120 Speaker 1: Well, they're really British universities are nothing like that now, 157 00:08:50,200 --> 00:08:53,400 Speaker 1: and then they were a million miles away from there. 158 00:08:53,480 --> 00:08:58,400 Speaker 1: So there were places like Cambridge whose colleges were immensely wealthy. 159 00:08:59,000 --> 00:09:01,920 Speaker 1: So you could walk on Trinity Land all the way 160 00:09:01,920 --> 00:09:05,040 Speaker 1: from Trinity College to the center of London. Wow. But 161 00:09:05,120 --> 00:09:08,480 Speaker 1: that did not accrue to the university, which was relatively poor. 162 00:09:09,280 --> 00:09:11,920 Speaker 1: And what had happened was that there was a five 163 00:09:12,000 --> 00:09:18,240 Speaker 1: year financial settlement every five years at Conquinium with the universities, 164 00:09:18,760 --> 00:09:22,800 Speaker 1: and unfortunately it was not indexed. So when we got 165 00:09:22,800 --> 00:09:26,280 Speaker 1: this burst of inflation in the early seventies, the universities 166 00:09:26,320 --> 00:09:30,200 Speaker 1: were going bankrupt. And Missus Stancher, I think it's not uncommon. 167 00:09:30,240 --> 00:09:32,520 Speaker 1: I mean, I don't think missus Stancher thought much of 168 00:09:32,640 --> 00:09:35,400 Speaker 1: sort of point he headed intellectuals, as it were, And 169 00:09:35,440 --> 00:09:38,640 Speaker 1: even though she'd been to Oxford to herself, and I 170 00:09:38,679 --> 00:09:40,880 Speaker 1: think it was probably true that most of the university 171 00:09:41,000 --> 00:09:42,680 Speaker 1: establishment was fairly hostile. 172 00:09:42,920 --> 00:09:46,880 Speaker 2: Are you finding after forty years here in the United States, 173 00:09:47,160 --> 00:09:50,680 Speaker 2: we're starting to see some criticism, at least in terms 174 00:09:50,720 --> 00:09:56,280 Speaker 2: of political correctness. And even what young and not particularly 175 00:09:56,280 --> 00:10:00,439 Speaker 2: experienced college students say about things in the Middle East 176 00:10:00,800 --> 00:10:05,000 Speaker 2: of Harvard was essentially shouted out of her office. How 177 00:10:05,000 --> 00:10:05,679 Speaker 2: do you look at this? 178 00:10:05,920 --> 00:10:10,600 Speaker 1: The mess that's happening in Israel and cause is something 179 00:10:10,800 --> 00:10:14,959 Speaker 1: very different, I think, and huge, and it's affecting all 180 00:10:15,000 --> 00:10:17,840 Speaker 1: parts of American society in ways that we really have 181 00:10:17,960 --> 00:10:21,000 Speaker 1: not seen before. But there's a sort of separate issue 182 00:10:21,480 --> 00:10:26,760 Speaker 1: of sort of political correctness within American universities. It's interesting that. 183 00:10:26,840 --> 00:10:31,319 Speaker 1: I mean, I taught at Princeton for more than thirty years. 184 00:10:31,640 --> 00:10:35,520 Speaker 1: I never encountered that at Princeton, So I never felt 185 00:10:35,760 --> 00:10:39,080 Speaker 1: that I had to issue trigger warnings or that students 186 00:10:39,120 --> 00:10:41,280 Speaker 1: wouldn't let me talk about certain things so they put 187 00:10:41,280 --> 00:10:42,920 Speaker 1: their hands out with their face when I said the 188 00:10:42,960 --> 00:10:44,000 Speaker 1: wrong words. 189 00:10:43,800 --> 00:10:46,160 Speaker 2: That really goes on in college. 190 00:10:46,000 --> 00:10:48,040 Speaker 1: Well, I'm told it does. But you know, I'm a 191 00:10:48,080 --> 00:10:50,720 Speaker 1: consumer of this, just as you are read about it 192 00:10:50,760 --> 00:10:54,600 Speaker 1: in the newspapers, and it makes me scared. I worry. 193 00:10:54,760 --> 00:10:58,680 Speaker 1: I have grandchildren to granddaughters at school in the city here, 194 00:10:59,000 --> 00:11:02,800 Speaker 1: and I wore by the political correctness of their teachers, 195 00:11:02,960 --> 00:11:05,640 Speaker 1: for example. But I haven't seen much of it in 196 00:11:05,679 --> 00:11:10,200 Speaker 1: the university so as far as Harvard, Mit pen et cetera. 197 00:11:10,640 --> 00:11:13,480 Speaker 1: I read about it in the newspapers. I don't have anything 198 00:11:13,480 --> 00:11:14,199 Speaker 1: original to say. 199 00:11:14,800 --> 00:11:17,360 Speaker 2: Maybe it's generational. But if I had a professor I 200 00:11:17,360 --> 00:11:20,640 Speaker 2: didn't like, I would go down to the registrar drop 201 00:11:20,720 --> 00:11:24,199 Speaker 2: the class. There was a market system there that if 202 00:11:24,240 --> 00:11:27,480 Speaker 2: you really said stuff that enough students didn't care for, 203 00:11:27,720 --> 00:11:29,920 Speaker 2: they wouldn't take your class. They'd take somebody else's. 204 00:11:30,000 --> 00:11:32,800 Speaker 1: That rarely happened to me. I remember one student who 205 00:11:32,800 --> 00:11:34,479 Speaker 1: didn't like the grade at given. 206 00:11:34,880 --> 00:11:35,840 Speaker 2: Way that it's too late. 207 00:11:36,040 --> 00:11:39,040 Speaker 1: It was too late, but I don't think she came 208 00:11:39,080 --> 00:11:40,679 Speaker 1: back for the second half of the course. 209 00:11:40,880 --> 00:11:43,760 Speaker 2: And then the other thing I have to ask you 210 00:11:43,800 --> 00:11:47,839 Speaker 2: about having grown up in the UK. What was your 211 00:11:47,880 --> 00:11:51,720 Speaker 2: experience like being an immigrant to the United States in 212 00:11:51,760 --> 00:11:56,480 Speaker 2: the nineteen eighties and having to adopt to a very 213 00:11:56,480 --> 00:12:01,000 Speaker 2: different set of economic circumstances. We'll talk more about healthcare, 214 00:12:01,080 --> 00:12:03,640 Speaker 2: which obviously is a world of difference. What we your 215 00:12:03,679 --> 00:12:06,679 Speaker 2: experience is like as a legal immigrant. 216 00:12:06,440 --> 00:12:11,920 Speaker 1: Legal Yeah, I was legitimate, documented alien. The initial title of. 217 00:12:11,840 --> 00:12:14,839 Speaker 2: That book was shock and Awe, really. 218 00:12:14,480 --> 00:12:16,480 Speaker 1: Which was in this sense, you know, I felt a 219 00:12:16,520 --> 00:12:19,320 Speaker 1: lot of awe at the amazing things that went on 220 00:12:19,840 --> 00:12:23,040 Speaker 1: in America and also a good deal of shock. So 221 00:12:23,080 --> 00:12:25,440 Speaker 1: the healthcare system was a big part of it, which 222 00:12:25,559 --> 00:12:27,760 Speaker 1: was sort of feeling that I didn't know how to 223 00:12:27,800 --> 00:12:31,160 Speaker 1: negotiate this. I didn't know the difference between a pediatrist 224 00:12:31,160 --> 00:12:34,560 Speaker 1: and a pediatrician, which turned out to be something I 225 00:12:34,600 --> 00:12:35,040 Speaker 1: had to know. 226 00:12:35,080 --> 00:12:38,959 Speaker 2: You had a GP, a general practitioner if you needed 227 00:12:38,960 --> 00:12:41,880 Speaker 2: something specific, they would send you that way. Or did 228 00:12:41,920 --> 00:12:43,440 Speaker 2: everybody do everything in the UK? 229 00:12:44,080 --> 00:12:47,600 Speaker 1: No, not everybody did everything, but the gps. The general 230 00:12:47,600 --> 00:12:52,600 Speaker 1: practitioners were gatekeepers too, you know, more advanced care or 231 00:12:52,640 --> 00:12:55,920 Speaker 1: specialized care, and I think that worked pretty well for us. 232 00:12:55,920 --> 00:12:58,000 Speaker 1: So that was quite a shock. I also liked having 233 00:12:58,000 --> 00:13:00,880 Speaker 1: a lot more money. That was certainly different, and I'd 234 00:13:00,880 --> 00:13:02,480 Speaker 1: worried about money my whole life. 235 00:13:03,120 --> 00:13:06,080 Speaker 2: Our professors higher paid in the United States than they 236 00:13:06,080 --> 00:13:06,680 Speaker 2: are in the UK. 237 00:13:07,720 --> 00:13:10,840 Speaker 1: They were then, for sure in Britain in those days, 238 00:13:10,880 --> 00:13:12,960 Speaker 1: pretty much all professors were paid the same and it 239 00:13:13,000 --> 00:13:16,000 Speaker 1: wasn't very much. Really, I had a lot more money. 240 00:13:15,800 --> 00:13:18,680 Speaker 2: Here in the United States. Yes, I have a vivid 241 00:13:18,800 --> 00:13:23,760 Speaker 2: recollection of being in the UK during the financial crisis 242 00:13:23,800 --> 00:13:26,560 Speaker 2: for work, and you walk down the streets from New 243 00:13:26,640 --> 00:13:30,440 Speaker 2: York in mid two thousand and eight, the tension is palpable, 244 00:13:30,960 --> 00:13:34,720 Speaker 2: and I didn't get that same sense in Europe. I 245 00:13:34,760 --> 00:13:37,400 Speaker 2: was in the UK and Brussels on one trip and 246 00:13:37,480 --> 00:13:41,360 Speaker 2: my conclusion was, Hey, if you're not stressing about losing 247 00:13:41,360 --> 00:13:44,320 Speaker 2: your healthcare because you're getting fired, it still sucks to 248 00:13:44,360 --> 00:13:47,760 Speaker 2: lose your job, but the stress level seems to be 249 00:13:47,800 --> 00:13:51,840 Speaker 2: a little less. Is that an oversimplification or is that a. 250 00:13:51,600 --> 00:13:54,880 Speaker 1: I hadn't noticed that, But it's certainly true that not 251 00:13:54,920 --> 00:13:57,960 Speaker 1: having to worry about healthcare is something that is a 252 00:13:57,960 --> 00:13:59,520 Speaker 1: big difference between the two much. 253 00:14:00,280 --> 00:14:04,079 Speaker 2: It's a huge burden, and when people do the comparison, 254 00:14:04,640 --> 00:14:06,760 Speaker 2: all right, you're paying a lot more taxes there. But 255 00:14:07,360 --> 00:14:11,080 Speaker 2: one of the biggest single contributors to inflation here, not 256 00:14:11,320 --> 00:14:14,600 Speaker 2: the past few years during the post COVID surge, but 257 00:14:14,679 --> 00:14:18,040 Speaker 2: the past forty years it's been growing at seven eight 258 00:14:18,160 --> 00:14:21,800 Speaker 2: nine percent. Your insurance costs and your hospital costs that's 259 00:14:21,840 --> 00:14:24,680 Speaker 2: a lot relative to two percent inflation rate. 260 00:14:24,720 --> 00:14:27,480 Speaker 1: Here, I'm a little time, and that's not happened in Britain, 261 00:14:27,520 --> 00:14:30,040 Speaker 1: and it hasn't happened in other European countries, and it 262 00:14:30,040 --> 00:14:33,840 Speaker 1: hasn't happened in Canada. It's just specifically specific to the 263 00:14:33,920 --> 00:14:36,000 Speaker 1: United States. And we could talk about some of the 264 00:14:36,040 --> 00:14:38,120 Speaker 1: reasons for that. But when I first came here, I mean, 265 00:14:38,160 --> 00:14:40,160 Speaker 1: the other bits about it that I really liked is, 266 00:14:40,600 --> 00:14:43,840 Speaker 1: you know, I worked with and got to know and 267 00:14:43,960 --> 00:14:46,960 Speaker 1: hung out with a lot of really great economists, and 268 00:14:47,040 --> 00:14:50,040 Speaker 1: I learned a ton. I deflected a little bit of 269 00:14:50,080 --> 00:14:53,240 Speaker 1: your question, but my interests are fairly eclectic, so I 270 00:14:53,320 --> 00:14:56,120 Speaker 1: work on a lot of different things. And at Princeton 271 00:14:56,160 --> 00:14:59,880 Speaker 1: I could always find some colleague who knew about X, 272 00:15:00,520 --> 00:15:04,040 Speaker 1: and X was something I'd just gotten interested in, whereas 273 00:15:04,200 --> 00:15:08,080 Speaker 1: in Britain that would have been much harder, really interdisciplinary 274 00:15:08,440 --> 00:15:11,040 Speaker 1: sort of thing, or even within the discipline, you know. 275 00:15:12,160 --> 00:15:14,120 Speaker 1: And some of it was the mathematics, you know, I 276 00:15:14,160 --> 00:15:16,560 Speaker 1: would have colleagues who knew how to do some obscure 277 00:15:16,600 --> 00:15:19,000 Speaker 1: piece of mathematics, or I would say, this person's using 278 00:15:19,040 --> 00:15:22,360 Speaker 1: this estimator, you know, how does that work? I remember 279 00:15:22,720 --> 00:15:25,920 Speaker 1: John Campbell and I when he was a young assistant professor. 280 00:15:25,920 --> 00:15:29,120 Speaker 1: He's now a very senior finance guy at Harvard. He 281 00:15:29,160 --> 00:15:32,280 Speaker 1: and I went down to the Engineering Library to discover 282 00:15:32,480 --> 00:15:37,040 Speaker 1: how what the spectrum at zero meant idea, and then 283 00:15:37,080 --> 00:15:38,640 Speaker 1: we used that in our work, you know. So it 284 00:15:38,680 --> 00:15:40,840 Speaker 1: was a wonderful place to do that, whereas at Bristol 285 00:15:40,840 --> 00:15:43,320 Speaker 1: it would be much harder. Quite apart from the fact 286 00:15:43,320 --> 00:15:45,840 Speaker 1: that at Bristol University of the library was unionized and 287 00:15:45,880 --> 00:15:48,320 Speaker 1: shut at four o'clock in the afternoon and was open 288 00:15:48,360 --> 00:15:48,920 Speaker 1: on weekend. 289 00:15:49,080 --> 00:15:52,080 Speaker 2: Wow. Plus, just off the top of my head. At 290 00:15:52,120 --> 00:15:55,640 Speaker 2: Princeton you had some guy named Ben Bernanke. I think 291 00:15:55,680 --> 00:15:56,400 Speaker 2: he did something. 292 00:15:57,760 --> 00:16:01,080 Speaker 1: I helped him. He came after I did. 293 00:16:01,400 --> 00:16:04,920 Speaker 2: That's amazing. And then Paul Krugman, another Nobel laureate, has 294 00:16:05,000 --> 00:16:08,000 Speaker 2: been there for the longest time. I think he now 295 00:16:08,080 --> 00:16:10,360 Speaker 2: is affiliated with City University. 296 00:16:09,920 --> 00:16:12,760 Speaker 1: That's right. And Chris Simms, who's a Nobel laureate, and 297 00:16:12,840 --> 00:16:15,600 Speaker 1: Danny Knneman was there and I worked with that. Danny 298 00:16:15,640 --> 00:16:18,440 Speaker 1: and I wrote a paper together. The one I don't 299 00:16:18,440 --> 00:16:21,880 Speaker 1: want to forget is Arthur Lewis, who got the Nobel 300 00:16:21,920 --> 00:16:25,160 Speaker 1: Prize the year I was visiting, and he remains the 301 00:16:25,200 --> 00:16:30,600 Speaker 1: only black scientific Nobel Laureate ever true. Yes, on the 302 00:16:30,640 --> 00:16:33,240 Speaker 1: others are peace laureates or literally. 303 00:16:33,760 --> 00:16:37,400 Speaker 2: So let's start with that subtitle. You call the US 304 00:16:37,600 --> 00:16:43,240 Speaker 2: the land of inequality. I'm not arguing with that premise. 305 00:16:43,280 --> 00:16:48,440 Speaker 2: I'm curious what led you to make that the subtitles. 306 00:16:48,760 --> 00:16:53,480 Speaker 2: Why is that so defining to the economy of the 307 00:16:53,560 --> 00:16:54,400 Speaker 2: United States. 308 00:16:54,840 --> 00:16:58,640 Speaker 1: Well, it's not just income inequality. It's inequality in many spaces. 309 00:16:59,040 --> 00:17:03,240 Speaker 1: So the qualities of extreme wealth and the extreme poverty 310 00:17:03,640 --> 00:17:06,520 Speaker 1: which seem to exist here. I mean, you have people 311 00:17:07,640 --> 00:17:11,480 Speaker 1: African Americans living along the Mississippi Delta who are probably 312 00:17:11,480 --> 00:17:14,880 Speaker 1: a poorest just about anyone in the world. And you know, 313 00:17:15,119 --> 00:17:17,720 Speaker 1: you have the richest people in the world, and you 314 00:17:17,800 --> 00:17:21,399 Speaker 1: don't seem to have quite those same extremes in Europe 315 00:17:21,440 --> 00:17:26,199 Speaker 1: the same extent. But if you come to inquality itself, 316 00:17:26,720 --> 00:17:31,080 Speaker 1: that's pretty why too. So you know, we economists like 317 00:17:31,119 --> 00:17:33,760 Speaker 1: to use things called Genie coefficients and so on, and 318 00:17:33,840 --> 00:17:36,760 Speaker 1: the Genie coefficients are you know, Americas are one of 319 00:17:36,760 --> 00:17:39,800 Speaker 1: the champion Genie coefficients. 320 00:17:39,560 --> 00:17:42,520 Speaker 2: Of fine Genie coefficients for the for the late people. 321 00:17:42,840 --> 00:17:45,880 Speaker 1: It's a measure of how far people are apart on average, 322 00:17:45,960 --> 00:17:48,480 Speaker 1: and unless you want the mathematics, that's a good way 323 00:17:48,480 --> 00:17:51,400 Speaker 1: of thinking about it, right. It's the sort of average 324 00:17:51,440 --> 00:17:54,680 Speaker 1: distance between any two pairs of people divided. 325 00:17:54,280 --> 00:17:57,080 Speaker 2: By the mean, the dispersion of wealth. 326 00:17:57,840 --> 00:18:02,600 Speaker 1: Yes, well or everybody so, and a lot of that 327 00:18:02,760 --> 00:18:05,800 Speaker 1: is good. You know. It is the land of opportunities, right, 328 00:18:06,160 --> 00:18:09,240 Speaker 1: and you know people are encouraged to get very, very rich, 329 00:18:09,480 --> 00:18:13,439 Speaker 1: and very rich people are celebrated in America. In Britain 330 00:18:13,440 --> 00:18:15,840 Speaker 1: where I grew up, they were described as fat cats, 331 00:18:16,320 --> 00:18:17,880 Speaker 1: and the newspapers really. 332 00:18:17,720 --> 00:18:20,240 Speaker 2: Like that here too, but that was the nineteen twenties. 333 00:18:20,280 --> 00:18:23,000 Speaker 1: Well, there's some truth to that. And as I think 334 00:18:23,040 --> 00:18:25,880 Speaker 1: I say in the book, in America, ordinary people seem 335 00:18:25,960 --> 00:18:27,920 Speaker 1: to like fat cats. They would like a dose of 336 00:18:28,040 --> 00:18:31,200 Speaker 1: feline obesity for themselves. 337 00:18:31,040 --> 00:18:33,879 Speaker 2: Which is which is a great line. You're implying something 338 00:18:33,880 --> 00:18:37,520 Speaker 2: I want to explore because I think you're onto something. 339 00:18:38,359 --> 00:18:42,359 Speaker 2: Are these two sides of the same coin? Is wealth 340 00:18:42,400 --> 00:18:49,199 Speaker 2: inequality and you know, greater riches than previously imagined? Do 341 00:18:49,320 --> 00:18:53,720 Speaker 2: these go hand in hand? And how does opportunity play 342 00:18:53,760 --> 00:18:54,200 Speaker 2: into that? 343 00:18:54,560 --> 00:18:58,760 Speaker 1: Well, that's something that people have thought about it in 344 00:18:58,840 --> 00:19:01,880 Speaker 1: economics for hundreds of years. Perhaps thousands of years really, 345 00:19:02,119 --> 00:19:04,760 Speaker 1: so that you know, these two things certainly aren't connected 346 00:19:04,880 --> 00:19:07,520 Speaker 1: for sure, And a lot of it's also got to 347 00:19:07,560 --> 00:19:10,199 Speaker 1: do with mobility. So societies that have a lot of 348 00:19:10,240 --> 00:19:14,880 Speaker 1: mobility tend to be relatively equal, where societies where everybody 349 00:19:14,960 --> 00:19:18,679 Speaker 1: inherits everything, like Britain land on a class in the 350 00:19:18,800 --> 00:19:20,000 Speaker 1: seventeenth century. 351 00:19:20,200 --> 00:19:24,720 Speaker 2: Although being landed gentry doesn't seem like a bad gig, No, it's. 352 00:19:24,640 --> 00:19:26,399 Speaker 1: Not a bad gig at all. But what happens if 353 00:19:26,400 --> 00:19:28,880 Speaker 1: you're the third son of a landed gentry and you're 354 00:19:28,880 --> 00:19:30,320 Speaker 1: in trouble. You're in trouble. 355 00:19:30,359 --> 00:19:31,359 Speaker 2: You better have some skills. 356 00:19:31,400 --> 00:19:33,760 Speaker 1: You're a lot of inequality there right for that sort 357 00:19:33,760 --> 00:19:35,320 Speaker 1: of thing, and that you. 358 00:19:35,240 --> 00:19:38,720 Speaker 2: Forget about prema geniture and the first son. We don't 359 00:19:38,760 --> 00:19:40,399 Speaker 2: really think in those terms. 360 00:19:40,400 --> 00:19:43,959 Speaker 1: In the States, maybe there's anyway. 361 00:19:44,600 --> 00:19:47,040 Speaker 2: But the other one, well, well, correct me if I'm wrong. 362 00:19:47,440 --> 00:19:50,520 Speaker 2: Is that more of a UK thing or do you 363 00:19:50,600 --> 00:19:52,440 Speaker 2: see parallels in the United States? 364 00:19:52,920 --> 00:19:56,199 Speaker 1: No, it's it's very much a UK thing, and it 365 00:19:56,280 --> 00:19:58,880 Speaker 1: goes with not just the UK but the European thing. 366 00:19:58,960 --> 00:20:01,479 Speaker 1: And like when the Tokeville came here, you know there 367 00:20:01,480 --> 00:20:03,520 Speaker 1: were none of those kings or jukes or all the 368 00:20:03,520 --> 00:20:06,680 Speaker 1: rest of it, and that was, you know, a big difference, 369 00:20:06,720 --> 00:20:11,199 Speaker 1: and that made them very unequal compared with here. So 370 00:20:11,400 --> 00:20:15,200 Speaker 1: America at its funding was a very equal place. And 371 00:20:15,280 --> 00:20:18,440 Speaker 1: you know, the finding fathers sort of assumed that democracy 372 00:20:18,560 --> 00:20:21,879 Speaker 1: would work and would require a fairly equal class of 373 00:20:22,080 --> 00:20:25,960 Speaker 1: artisans and farmers and so on. So it was only 374 00:20:26,000 --> 00:20:29,320 Speaker 1: when it became a sort of industrial society and finance 375 00:20:29,400 --> 00:20:31,320 Speaker 1: crept in and so on, then you begin to get 376 00:20:31,320 --> 00:20:35,320 Speaker 1: these normous spread Now that's the good side of it. 377 00:20:36,080 --> 00:20:41,760 Speaker 1: You know, it's very hard to complain about people who 378 00:20:41,800 --> 00:20:45,440 Speaker 1: get rich in the public interest, right, so who do 379 00:20:45,520 --> 00:20:50,359 Speaker 1: things that help spread wet wealth around that creates jobs, 380 00:20:50,400 --> 00:20:53,000 Speaker 1: that makes other people well love to But there's a 381 00:20:53,080 --> 00:20:56,640 Speaker 1: potential dark site, which is the takers, as it were, 382 00:20:57,119 --> 00:21:00,639 Speaker 1: the people who use government or who use regulars or 383 00:21:00,680 --> 00:21:05,639 Speaker 1: you would lose lobbying. For example, the term that we 384 00:21:05,720 --> 00:21:09,280 Speaker 1: economists tend to use is rent seeking rather than rentiers. 385 00:21:09,320 --> 00:21:11,200 Speaker 1: I mean a rent here is someone who owns land 386 00:21:11,200 --> 00:21:14,400 Speaker 1: and rents it out right, whereas or someone who lives 387 00:21:14,400 --> 00:21:17,520 Speaker 1: off capital. But rent seeking is people who use the 388 00:21:17,560 --> 00:21:21,119 Speaker 1: political system to try and butter their bread a little 389 00:21:21,160 --> 00:21:23,920 Speaker 1: more thickly and of course you get that in Britain too, 390 00:21:24,040 --> 00:21:28,119 Speaker 1: I mean the corn Laws, which were you know, you 391 00:21:28,160 --> 00:21:31,680 Speaker 1: had an aristocratic land owning class who passed the corn 392 00:21:31,760 --> 00:21:35,040 Speaker 1: laws to keep the price of grain up and that's 393 00:21:35,040 --> 00:21:40,560 Speaker 1: what they lived off, was growing wheat and selling it. 394 00:21:40,680 --> 00:21:44,120 Speaker 1: But here you worry a lot about people getting rich 395 00:21:44,240 --> 00:21:49,480 Speaker 1: through lobbying, through restrictive practices, minor ones, major ones. You 396 00:21:49,560 --> 00:21:52,560 Speaker 1: worry about the way that banks sometimes behave. I mean, 397 00:21:52,600 --> 00:21:56,359 Speaker 1: our banks really sucking blood from the rest of us 398 00:21:56,400 --> 00:21:59,080 Speaker 1: sort of ideas. Some people tend to think we need 399 00:21:59,160 --> 00:22:02,320 Speaker 1: banks are very important, but banks and then of course 400 00:22:02,320 --> 00:22:04,760 Speaker 1: you got this healthcare system that seems to be making 401 00:22:04,760 --> 00:22:07,000 Speaker 1: a huge amount of money, which they don't make in 402 00:22:07,040 --> 00:22:09,600 Speaker 1: other countries. And there's a lot of people get paid 403 00:22:09,720 --> 00:22:12,560 Speaker 1: huge sums of money, a lot of stuff that's being done. 404 00:22:12,720 --> 00:22:16,480 Speaker 1: So that's the negative side of high inequality, which is 405 00:22:16,480 --> 00:22:19,480 Speaker 1: an equality not doing anyone any good. Sometimes we talk 406 00:22:19,480 --> 00:22:23,120 Speaker 1: about takers versus makers, uh huh, And you know makers 407 00:22:23,160 --> 00:22:30,080 Speaker 1: are good and they benefit everybody, but takers are not good. 408 00:22:30,200 --> 00:22:31,359 Speaker 1: They're stealing from people. 409 00:22:32,280 --> 00:22:34,800 Speaker 2: So let's there's so many different ways to go with this. 410 00:22:35,480 --> 00:22:38,000 Speaker 2: Why don't we talk first before we get to healthcare. 411 00:22:38,080 --> 00:22:42,119 Speaker 2: Let's talk about minimum wage. Okay, all right. So carden 412 00:22:42,200 --> 00:22:46,960 Speaker 2: Krueger very famously wrote a paper about changing in the 413 00:22:46,960 --> 00:22:50,680 Speaker 2: minimum wage. They were looking at fast food restaurants in 414 00:22:50,760 --> 00:22:53,920 Speaker 2: southern New Jersey and Pennsylvania. I think New Jersey had 415 00:22:53,960 --> 00:22:56,480 Speaker 2: an increase in the minimum wage. And it's not like 416 00:22:56,600 --> 00:22:59,640 Speaker 2: there's a very robust border there. You can hardly tell 417 00:22:59,640 --> 00:23:03,199 Speaker 2: when you're one area or the other. It didn't the 418 00:23:03,320 --> 00:23:07,600 Speaker 2: rising minimum wage. A modest increase in minimum wage did 419 00:23:07,680 --> 00:23:10,480 Speaker 2: not seem, according to the data, to cause an increase 420 00:23:10,520 --> 00:23:15,639 Speaker 2: in unemployment, as was widely predicted. They got pushback on 421 00:23:15,680 --> 00:23:19,920 Speaker 2: that paper for literally decades before card won the Nobel 422 00:23:19,960 --> 00:23:21,640 Speaker 2: Prize in was that twenty one. 423 00:23:21,800 --> 00:23:26,280 Speaker 1: I'm not sure it's died down. I quote Jason Furman 424 00:23:26,400 --> 00:23:30,359 Speaker 1: as saying, even today they persuaded about half of the profession, 425 00:23:30,359 --> 00:23:32,560 Speaker 1: and the other half of the profession think it's not right. 426 00:23:33,000 --> 00:23:35,880 Speaker 1: It's important too. They wrote a book called method Measurement, 427 00:23:36,320 --> 00:23:38,919 Speaker 1: which had many studies in it, and they did a 428 00:23:38,960 --> 00:23:42,959 Speaker 1: really very good job of reconciling their findings and other findings. 429 00:23:43,359 --> 00:23:45,920 Speaker 1: And that's in some ways much more important work. I mean, 430 00:23:46,560 --> 00:23:50,359 Speaker 1: the Pennsylvania New Jersey thing, it sounds like, you know, 431 00:23:50,440 --> 00:23:52,960 Speaker 1: ones on either side of the Delaware water gap sort 432 00:23:52,960 --> 00:23:55,960 Speaker 1: of idea. But some of the New Jersey restaurants were 433 00:23:55,960 --> 00:23:58,119 Speaker 1: on the shore and some of the Pennsylvania ones were 434 00:23:58,119 --> 00:24:00,879 Speaker 1: in Pittsburgh or something, you know, So there were a 435 00:24:00,920 --> 00:24:06,960 Speaker 1: lot of and what should happened was they what happened 436 00:24:07,040 --> 00:24:12,520 Speaker 1: was not. There was certainly no decrease in employment in 437 00:24:12,560 --> 00:24:16,840 Speaker 1: New Jersey. There was a decrease in employment. Sorry, yes, 438 00:24:16,920 --> 00:24:19,800 Speaker 1: there was a decrease in employment in Pennsylvania. 439 00:24:19,280 --> 00:24:20,359 Speaker 2: A rise in unemployment. 440 00:24:20,480 --> 00:24:22,639 Speaker 1: So when you compared the difference of the two, it 441 00:24:23,720 --> 00:24:26,679 Speaker 1: was quite large, and it went in the opposite direction 442 00:24:26,800 --> 00:24:29,000 Speaker 1: to what people have predicted. But the action was actually 443 00:24:29,080 --> 00:24:32,720 Speaker 1: in Philadelphia, in Pennsylvania rather than in New Jersey. But 444 00:24:32,840 --> 00:24:36,200 Speaker 1: in their book and in dozens and dozens and dozens 445 00:24:36,240 --> 00:24:41,280 Speaker 1: of studies since, that result has been pretty strongly replicated 446 00:24:41,800 --> 00:24:45,120 Speaker 1: that for modest increases in the minimum wage, it does 447 00:24:45,160 --> 00:24:49,400 Speaker 1: not give rise to increases unemployment. 448 00:24:49,560 --> 00:24:52,080 Speaker 2: If you just stop and think about it for a moment, 449 00:24:52,680 --> 00:24:56,360 Speaker 2: if you're paying the poorest or the lowest paid people 450 00:24:57,040 --> 00:25:00,240 Speaker 2: in a region a dollar or two more in an hour, 451 00:25:00,800 --> 00:25:03,400 Speaker 2: they're just going to go out and spend that on 452 00:25:03,640 --> 00:25:06,280 Speaker 2: you know, frivolous things like food and medicine and rent. 453 00:25:06,520 --> 00:25:12,080 Speaker 2: But if if you are freezing that so that the 454 00:25:12,119 --> 00:25:15,440 Speaker 2: profits are higher for either the corporation or the franchise owner, 455 00:25:15,920 --> 00:25:18,679 Speaker 2: that's probably not going to be spent locally. It's going 456 00:25:18,720 --> 00:25:21,560 Speaker 2: to be saved or invested, but that'll be elsewhere. It 457 00:25:21,600 --> 00:25:24,560 Speaker 2: won't be in that local town. I would assume the 458 00:25:24,680 --> 00:25:27,520 Speaker 2: higher salary is just going to stimulate the local economy. 459 00:25:28,280 --> 00:25:30,560 Speaker 2: Is that an oversimplification of what they found or is 460 00:25:30,560 --> 00:25:30,879 Speaker 2: that no? 461 00:25:31,000 --> 00:25:33,520 Speaker 1: I think that's there, but I don't think they would 462 00:25:33,520 --> 00:25:35,439 Speaker 1: have thought of that as the major effect. I mean, 463 00:25:35,480 --> 00:25:38,240 Speaker 1: after all of that, that many fast food workers in 464 00:25:38,680 --> 00:25:42,160 Speaker 1: you know, Pennsylvania, and compared with everyone, so the amount 465 00:25:42,160 --> 00:25:45,080 Speaker 1: of extra money they get from the minimum wage is 466 00:25:45,119 --> 00:25:46,880 Speaker 1: going to be pretty small relative to the size. 467 00:25:47,080 --> 00:25:49,119 Speaker 2: I drive down the New Jersey Turnpike, it looks like 468 00:25:49,240 --> 00:25:51,399 Speaker 2: ninety percent of the people are working in fast foods. 469 00:25:51,480 --> 00:25:54,040 Speaker 1: Well, that's because you're on the New Jersey Turnpike, you know. 470 00:25:55,280 --> 00:25:57,240 Speaker 1: For in Princeton for a long time, they wouldn't let 471 00:25:57,320 --> 00:26:00,399 Speaker 1: fast food joints in the town. Right There are a 472 00:26:00,400 --> 00:26:03,639 Speaker 1: few places, snooty places, Yeah, there are a few. So 473 00:26:03,680 --> 00:26:08,040 Speaker 1: it's a small impact on the macro economy the local. 474 00:26:08,240 --> 00:26:12,280 Speaker 2: On the local economy. Why is this is the assumption just, hey, 475 00:26:12,280 --> 00:26:14,840 Speaker 2: if you make us pay more per hour, we're going 476 00:26:14,880 --> 00:26:15,960 Speaker 2: to hire less workers. 477 00:26:16,160 --> 00:26:19,080 Speaker 1: Well, that's the belief, and that's what happens in textbook 478 00:26:19,119 --> 00:26:22,000 Speaker 1: models of labor markets. It's just that the textbook model 479 00:26:22,040 --> 00:26:24,239 Speaker 1: doesn't do a very good job. But there's a very 480 00:26:24,280 --> 00:26:27,600 Speaker 1: important issue with this that I talk about in the book. 481 00:26:28,160 --> 00:26:31,639 Speaker 1: And I think this over the last of the years 482 00:26:31,680 --> 00:26:34,320 Speaker 1: since that paper was written and that book was written, 483 00:26:34,920 --> 00:26:37,600 Speaker 1: not only has there been a lot of replication, but 484 00:26:37,680 --> 00:26:41,960 Speaker 1: what it's suggesting is there really is some surplus in 485 00:26:42,280 --> 00:26:47,000 Speaker 1: these joints which could be dedicated to either profits or 486 00:26:48,600 --> 00:26:49,880 Speaker 1: labor wages. 487 00:26:50,400 --> 00:26:53,679 Speaker 2: In other words, they're not working on such a tight 488 00:26:53,960 --> 00:26:56,200 Speaker 2: margin that there is a little buffer. 489 00:26:56,440 --> 00:27:00,320 Speaker 1: Well that what economists call that is monopsony, which means 490 00:27:00,320 --> 00:27:02,800 Speaker 1: they have some power over the workers, so they can 491 00:27:02,840 --> 00:27:06,000 Speaker 1: actually deliberately lower their wages because it's hard for the 492 00:27:06,080 --> 00:27:09,840 Speaker 1: workers to go somewhere else Whereas in the textbook, if 493 00:27:09,840 --> 00:27:15,240 Speaker 1: you lower someone's wage below the prevailing wage, those people 494 00:27:15,520 --> 00:27:17,080 Speaker 1: will just vanish. 495 00:27:17,359 --> 00:27:18,240 Speaker 2: They'll quit the job. 496 00:27:18,359 --> 00:27:21,560 Speaker 1: They'll quit the job. So what you've got here is 497 00:27:22,720 --> 00:27:25,840 Speaker 1: there is monopsony in that you can force people's wages 498 00:27:25,960 --> 00:27:28,120 Speaker 1: down and it's hard for them to move. 499 00:27:29,080 --> 00:27:31,639 Speaker 2: I love that word, which I think I don't remember 500 00:27:31,640 --> 00:27:34,240 Speaker 2: if you mentioned it or I just know her work. 501 00:27:34,359 --> 00:27:37,760 Speaker 2: Joan Robinson. She has one of my all time favorite 502 00:27:37,840 --> 00:27:42,439 Speaker 2: quotes about economics, which is, we study economics not to 503 00:27:42,520 --> 00:27:44,919 Speaker 2: predict the future, but so as to not be fooled 504 00:27:44,960 --> 00:27:49,320 Speaker 2: by economists. There's a that's just so full of insight 505 00:27:49,520 --> 00:27:54,000 Speaker 2: and so interesting. I think she's finally getting her due 506 00:27:54,040 --> 00:27:57,520 Speaker 2: these days, and she hadn't for a long time. Let's 507 00:27:57,520 --> 00:28:04,560 Speaker 2: stay with minimum wage, you implied, this still isn't accepted. 508 00:28:04,600 --> 00:28:08,440 Speaker 2: There's a Nobel Prize to card and I guess indirectly 509 00:28:08,680 --> 00:28:13,639 Speaker 2: to Kruger. There's tons and tons of studies that have 510 00:28:13,920 --> 00:28:18,119 Speaker 2: validated their original research. There still seems to be a 511 00:28:18,160 --> 00:28:22,119 Speaker 2: lot of resistance to accepting those facts. Is this a 512 00:28:22,200 --> 00:28:25,960 Speaker 2: case I forgot what physicist I'm stealing this from Physics 513 00:28:26,040 --> 00:28:29,000 Speaker 2: Advances One funeral at a time is the same thing 514 00:28:29,040 --> 00:28:30,679 Speaker 2: taking place in economics? 515 00:28:30,760 --> 00:28:33,520 Speaker 1: There may be some of that. I think it's rather 516 00:28:33,600 --> 00:28:36,199 Speaker 1: more than a half. And in Britain, where they have 517 00:28:36,240 --> 00:28:40,800 Speaker 1: a much much higher minimum wage than here. It's supported 518 00:28:40,840 --> 00:28:42,760 Speaker 1: by everyone on the right and the left. 519 00:28:42,960 --> 00:28:45,920 Speaker 2: Really, yes, is it thinking, Hey, if the companies pay 520 00:28:45,960 --> 00:28:47,560 Speaker 2: for it, well, then it's not on the government to 521 00:28:47,600 --> 00:28:47,959 Speaker 2: cover it. 522 00:28:48,160 --> 00:28:50,200 Speaker 1: That I think is an important part of the story. 523 00:28:50,920 --> 00:28:53,360 Speaker 1: And I don't think they have the lobby that they 524 00:28:53,440 --> 00:28:56,560 Speaker 1: have here by the fast food industry to help keep 525 00:28:56,600 --> 00:28:57,240 Speaker 1: wages done. 526 00:28:57,840 --> 00:28:59,040 Speaker 2: And that's a big deal. 527 00:28:59,200 --> 00:29:04,280 Speaker 1: A lot of the opposition against carden Kruger was from 528 00:29:04,360 --> 00:29:07,360 Speaker 1: the EPI, which is a lobby against cute for Faster. 529 00:29:07,520 --> 00:29:10,840 Speaker 2: Now that changed. EPI is also the economic policy and 530 00:29:12,120 --> 00:29:18,440 Speaker 2: one that's very funny. I recall about a decade ago 531 00:29:18,600 --> 00:29:22,600 Speaker 2: looking at minimum wage and it hadn't increased in a while, 532 00:29:23,240 --> 00:29:26,600 Speaker 2: and the big opponents were not just fast food, but 533 00:29:26,760 --> 00:29:31,280 Speaker 2: the big box retailers like Walmart. And what's kind of ironic, 534 00:29:32,120 --> 00:29:37,600 Speaker 2: by fighting minimum wage, they ended up giving the upstart 535 00:29:37,840 --> 00:29:41,320 Speaker 2: Amazon an opportunity. At one point, I want to say, 536 00:29:41,320 --> 00:29:45,080 Speaker 2: this is about five six, seven years ago, Amazon just 537 00:29:45,120 --> 00:29:47,959 Speaker 2: said our minimum is fifteen dollars an hour. They went 538 00:29:48,000 --> 00:29:50,800 Speaker 2: out and scooped up all the best people in areas 539 00:29:50,440 --> 00:29:56,880 Speaker 2: for warehouses and delivery, and suddenly places like Walmart were scrambling, 540 00:29:57,200 --> 00:29:59,080 Speaker 2: and there was a long period of time where Walmart 541 00:29:59,080 --> 00:30:02,120 Speaker 2: couldn't get enough w workers to stock their shelves. It 542 00:30:02,800 --> 00:30:04,800 Speaker 2: ultimately they ended up hurting themselves. 543 00:30:05,000 --> 00:30:07,360 Speaker 1: Yep. But another part of this that is very important 544 00:30:07,480 --> 00:30:10,360 Speaker 1: is most states or I don't know what fraction of 545 00:30:10,360 --> 00:30:14,080 Speaker 1: American above the federal minimum wages that are above the 546 00:30:14,120 --> 00:30:17,320 Speaker 1: federal ones. It's also true that something like seventy percent 547 00:30:17,360 --> 00:30:19,920 Speaker 1: of Americans would like to see a higher minimum way 548 00:30:20,240 --> 00:30:22,960 Speaker 1: seventy percent. That's the sort of number that comes out 549 00:30:23,000 --> 00:30:25,240 Speaker 1: in these polls. I haven't looked at the most recent one. 550 00:30:25,760 --> 00:30:28,200 Speaker 1: And yet you know it doesn't go through in Washington 551 00:30:28,280 --> 00:30:31,120 Speaker 1: because the lobbyists are very powerful and they're you know, 552 00:30:31,320 --> 00:30:33,560 Speaker 1: paying campaign contributions and all the rest of it. 553 00:30:34,320 --> 00:30:35,760 Speaker 2: I mean, it wouldn't be the worst thing in the 554 00:30:35,760 --> 00:30:40,000 Speaker 2: world if your taco bell or your McDonald's cost a 555 00:30:40,040 --> 00:30:43,719 Speaker 2: buck or so more. We're all going to end up 556 00:30:43,720 --> 00:30:48,600 Speaker 2: paying for it through Medicare Medicaid eventually, right indirectly between 557 00:30:48,640 --> 00:30:51,920 Speaker 2: diabetes and god knows what else in a country that 558 00:30:52,000 --> 00:30:55,280 Speaker 2: has our healthcare issues. So let's transition. Let's talk a 559 00:30:55,320 --> 00:31:00,280 Speaker 2: little bit about healthcare. Okay, in the UK, it's cradle great, right, 560 00:31:00,320 --> 00:31:03,680 Speaker 2: You're covered from you're born a UK citizen, you got 561 00:31:03,680 --> 00:31:05,280 Speaker 2: full healthcare coverage. 562 00:31:05,000 --> 00:31:08,240 Speaker 1: Not for there are some things where you have to pay, 563 00:31:09,120 --> 00:31:15,000 Speaker 1: like prescriptions prescription drugs, but very heavily subsidized, and also 564 00:31:15,280 --> 00:31:17,600 Speaker 1: you have to wait. And so there's a lot of 565 00:31:17,640 --> 00:31:20,960 Speaker 1: private healthcare in Britain where people avoid the lines. 566 00:31:21,800 --> 00:31:24,520 Speaker 2: So if you how bad are the lines, well, it. 567 00:31:24,520 --> 00:31:28,600 Speaker 1: Depends where you are and it can be quite soon, 568 00:31:28,640 --> 00:31:30,280 Speaker 1: but you might have to wait a couple of years 569 00:31:30,320 --> 00:31:32,720 Speaker 1: to get a hip replace for you. Really, and the 570 00:31:32,760 --> 00:31:33,880 Speaker 1: same is true in Canada. 571 00:31:34,040 --> 00:31:35,560 Speaker 2: I was going to ask because I've heard the same 572 00:31:35,600 --> 00:31:40,160 Speaker 2: thing in Canada about both things about some of the 573 00:31:40,160 --> 00:31:43,960 Speaker 2: weights for specific surgeries and the rise of this sort 574 00:31:44,000 --> 00:31:48,160 Speaker 2: of concierge medicine for the people who can afford it, 575 00:31:48,440 --> 00:31:50,760 Speaker 2: they wait a week to get in to see a doctor. 576 00:31:50,800 --> 00:31:55,360 Speaker 1: If that a lot of people in America have concierge medicine, Yeah, they. 577 00:31:55,240 --> 00:32:02,720 Speaker 2: Have, so clearly it's it's a you difference. Ultimately in 578 00:32:02,800 --> 00:32:07,600 Speaker 2: canon and the UK you're paying for that through higher taxes, but. 579 00:32:07,600 --> 00:32:09,760 Speaker 1: It only costs half as much as the charegy. 580 00:32:10,040 --> 00:32:12,560 Speaker 2: So that's where I was going to go. Why if 581 00:32:12,560 --> 00:32:16,920 Speaker 2: the US has the supposedly more efficient private sector, then 582 00:32:17,080 --> 00:32:22,040 Speaker 2: big slow, incompetent, bureaucratic government. Why does US healthcare cost 583 00:32:22,200 --> 00:32:24,480 Speaker 2: twice as much as the rest of the world and 584 00:32:25,120 --> 00:32:26,520 Speaker 2: create worse outcomes. 585 00:32:26,920 --> 00:32:29,239 Speaker 1: Well, because it's full of rent seecrets, which is what 586 00:32:29,240 --> 00:32:31,320 Speaker 1: we were talking about before. I mean, there's a lot 587 00:32:31,360 --> 00:32:35,920 Speaker 1: of people getting very wealthy out of that. Their device manufacturers, 588 00:32:36,000 --> 00:32:40,200 Speaker 1: they're pharma companies. There's hospitals which are a huge part 589 00:32:40,240 --> 00:32:44,120 Speaker 1: of this. Also, remember if you're in the UK and 590 00:32:44,160 --> 00:32:48,480 Speaker 1: the government pays for everything, there's no insurance industry. Uh huh, right, 591 00:32:48,600 --> 00:32:52,040 Speaker 1: So that insurance industry is a big chunk of change. 592 00:32:52,400 --> 00:32:55,600 Speaker 1: And it's not their profits they're making it so expensive though, 593 00:32:55,640 --> 00:32:58,160 Speaker 1: that's in there too, But it's just that they exist. 594 00:32:58,760 --> 00:33:01,640 Speaker 2: There's a giant middleman between the doctor and the patient. 595 00:33:01,360 --> 00:33:03,720 Speaker 1: Who's spending a lot of time trying to stop the 596 00:33:04,000 --> 00:33:05,680 Speaker 1: stop you getting the healthcare you need. 597 00:33:06,400 --> 00:33:11,560 Speaker 2: That is very true. My personal experience has been insurers 598 00:33:11,600 --> 00:33:15,960 Speaker 2: are very happy not to have you do anything. To 599 00:33:16,160 --> 00:33:18,960 Speaker 2: be fair, A lot of times people will make an 600 00:33:19,000 --> 00:33:21,560 Speaker 2: appointment and it's a month off and by the time 601 00:33:21,640 --> 00:33:24,400 Speaker 2: the month rolls away. The issue is especially if it's 602 00:33:24,400 --> 00:33:27,400 Speaker 2: like a sports injury, but if you have something really 603 00:33:27,480 --> 00:33:31,960 Speaker 2: serious don't we want people to get in and engage 604 00:33:32,000 --> 00:33:34,360 Speaker 2: in preventive medicine before it gets worse. 605 00:33:34,840 --> 00:33:39,680 Speaker 1: It's not entirely clear. Preventive medicine sounds like a great idea, 606 00:33:39,760 --> 00:33:42,840 Speaker 1: but it's not always such a great idea. So, for instance, 607 00:33:42,880 --> 00:33:45,080 Speaker 1: one of the thing about prevented medsine I worry about 608 00:33:45,120 --> 00:33:47,880 Speaker 1: a lot is smart watches for it, right, So if 609 00:33:47,920 --> 00:33:49,400 Speaker 1: you got one of those, you're going to get all 610 00:33:49,400 --> 00:33:52,440 Speaker 1: sorts of false positives, right, and you're going to spend 611 00:33:52,440 --> 00:33:56,920 Speaker 1: a huge amount of time getting tests for things that 612 00:33:57,680 --> 00:34:02,480 Speaker 1: you know you probably don't have. And so prevented medicine 613 00:34:02,520 --> 00:34:05,320 Speaker 1: of that sort can cost a lot of money. There 614 00:34:05,320 --> 00:34:10,200 Speaker 1: are types of prevented medicine like taking anti hypertensives or 615 00:34:10,280 --> 00:34:13,920 Speaker 1: taking statins, for instance, which save an enormous number of lives. 616 00:34:13,920 --> 00:34:17,040 Speaker 1: They don't cost hardly anything, and those have been the 617 00:34:17,080 --> 00:34:22,280 Speaker 1: things that have been largely responsible for the rapidly increase 618 00:34:22,400 --> 00:34:25,800 Speaker 1: well the decrease in mortality and the increase in life 619 00:34:25,840 --> 00:34:29,520 Speaker 1: expectancy in the last quarter of the twentieth century. 620 00:34:30,239 --> 00:34:34,720 Speaker 2: I sort not the studies themselves, but some articles about 621 00:34:34,719 --> 00:34:38,440 Speaker 2: them that found there are all these proactive things that 622 00:34:38,520 --> 00:34:42,680 Speaker 2: are a little expensive that insurers could do, but they 623 00:34:42,760 --> 00:34:47,279 Speaker 2: don't because their experience has been the average person switches 624 00:34:47,560 --> 00:34:50,240 Speaker 2: either insurers or jobs, and therefore you're going to switch 625 00:34:50,800 --> 00:34:54,160 Speaker 2: your coverage provider something like every four point seven years, 626 00:34:54,760 --> 00:34:57,920 Speaker 2: and if the payoff for these expensive preventive things are 627 00:34:58,360 --> 00:35:00,960 Speaker 2: seven to ten years down the world road, they have 628 00:35:01,040 --> 00:35:02,080 Speaker 2: no incentive to do it. 629 00:35:02,239 --> 00:35:05,600 Speaker 1: I didn't I haven't seen that, but it sounds entirely plausible. 630 00:35:05,840 --> 00:35:07,520 Speaker 2: It was just kind of, hey, don't you want to 631 00:35:07,560 --> 00:35:09,800 Speaker 2: prevent these No, they're not going to be a client 632 00:35:09,800 --> 00:35:12,160 Speaker 2: in five years, so I mean, yeah, well that could be. 633 00:35:12,560 --> 00:35:16,000 Speaker 2: What other factors do you observe about healthcare in the 634 00:35:16,080 --> 00:35:17,520 Speaker 2: United States versus elsewhere? 635 00:35:17,600 --> 00:35:21,879 Speaker 1: Well, the major thing my colleague, my late colleague, Ryan Hart, 636 00:35:22,000 --> 00:35:24,719 Speaker 1: who is our sort of local healthcare expert, and it 637 00:35:24,800 --> 00:35:29,239 Speaker 1: was a very fine researcher and lecturer, is a very 638 00:35:29,280 --> 00:35:33,200 Speaker 1: funny man, very witty man. He wrote a book called 639 00:35:33,200 --> 00:35:36,640 Speaker 1: It's the Price is Stupid sort of idea, and the 640 00:35:36,760 --> 00:35:39,439 Speaker 1: argument is that almost everything in the US costs about 641 00:35:39,480 --> 00:35:42,279 Speaker 1: twice as much as it costs another country. Really, yeah, 642 00:35:42,320 --> 00:35:44,239 Speaker 1: so all these drugs, you know. 643 00:35:44,160 --> 00:35:45,360 Speaker 2: Everything healthcare related. 644 00:35:45,360 --> 00:35:47,799 Speaker 1: You're saying, yeah, everything healthcare. So if you look at 645 00:35:47,800 --> 00:35:49,799 Speaker 1: the price of drugs, and you can look at the 646 00:35:49,840 --> 00:35:52,560 Speaker 1: identical drugs, and you can look at them across countries, 647 00:35:52,560 --> 00:35:55,480 Speaker 1: and there's any number of papers who've done this, you know, 648 00:35:55,520 --> 00:35:57,800 Speaker 1: in the New England Journal of Medicine and the JAMMA 649 00:35:57,920 --> 00:36:01,440 Speaker 1: and so on, and you know they costs. The same 650 00:36:01,600 --> 00:36:04,800 Speaker 1: company is selling the same drug at twice the price, 651 00:36:04,840 --> 00:36:07,600 Speaker 1: are more than twice the price here than they do 652 00:36:08,280 --> 00:36:11,920 Speaker 1: in other countries. Now, in Britain, for instance, they have 653 00:36:11,960 --> 00:36:15,279 Speaker 1: a thing called NICE, which is the National Institute for 654 00:36:15,400 --> 00:36:18,920 Speaker 1: Healthcare Excellence or something, and what they do is they 655 00:36:18,960 --> 00:36:22,479 Speaker 1: evaluate new drugs and they look, they do a cost 656 00:36:22,520 --> 00:36:27,280 Speaker 1: benefit test and they disallow it if it doesn't save 657 00:36:27,440 --> 00:36:30,760 Speaker 1: enough lives as it were, or cause enough extra health 658 00:36:31,239 --> 00:36:35,280 Speaker 1: route per dollar. So then what happens is the farmer companies, 659 00:36:35,320 --> 00:36:37,520 Speaker 1: if they want to sell it in Britain, they reduce 660 00:36:37,600 --> 00:36:40,600 Speaker 1: the price to meet that cut off. Right in America 661 00:36:40,640 --> 00:36:43,000 Speaker 1: they don't. They charge the full freight, so it just 662 00:36:43,040 --> 00:36:45,480 Speaker 1: costs a lot more. There are arguments for that that 663 00:36:45,520 --> 00:36:47,719 Speaker 1: you hear from the farmer companies all the time, which 664 00:36:47,719 --> 00:36:51,160 Speaker 1: they say, we're doing their research here, and you know 665 00:36:51,160 --> 00:36:54,640 Speaker 1: Britain is just piggybacking off that I think those arguments 666 00:36:54,680 --> 00:36:57,759 Speaker 1: are wearing a little bit thin nowadays, but it's I 667 00:36:57,840 --> 00:36:58,919 Speaker 1: can't disprove that. 668 00:36:59,800 --> 00:37:03,560 Speaker 2: Do any other countries. And I don't watch a whole 669 00:37:03,600 --> 00:37:07,320 Speaker 2: lot of television commercials. Everything I watch is either streaming 670 00:37:07,440 --> 00:37:10,080 Speaker 2: or DVR, so I fast forward through it. But it 671 00:37:10,160 --> 00:37:14,640 Speaker 2: seems every other commercial is for some pharma product. When 672 00:37:14,640 --> 00:37:19,239 Speaker 2: I was a kid, none of these obscure medicines advertised 673 00:37:19,280 --> 00:37:23,080 Speaker 2: on TV. I still don't even know who asked their 674 00:37:23,120 --> 00:37:28,640 Speaker 2: physicists about restless leg syndrome. Their physician, right, their physician, 675 00:37:28,760 --> 00:37:32,319 Speaker 2: not their physicists. But it just seems sort of bizarre 676 00:37:32,360 --> 00:37:35,440 Speaker 2: that we have all these ads. Does any other country 677 00:37:35,440 --> 00:37:35,920 Speaker 2: in the world. 678 00:37:36,120 --> 00:37:38,880 Speaker 1: I think there's a one, which it may be New Zealand, 679 00:37:38,920 --> 00:37:41,600 Speaker 1: either New Zealand or Australia forget me. And that's illegal 680 00:37:42,120 --> 00:37:45,120 Speaker 1: everywhere else in the rich world. And it's true. I 681 00:37:45,160 --> 00:37:47,000 Speaker 1: went along to my doctor and he said, well, you know, 682 00:37:47,040 --> 00:37:49,000 Speaker 1: if you're a pregnant woman, maybe it would be a 683 00:37:49,040 --> 00:37:53,000 Speaker 1: good idea, but you're not, so we don't really need that. 684 00:37:53,320 --> 00:37:55,040 Speaker 1: But that's part of it. The other part of it 685 00:37:55,080 --> 00:37:59,960 Speaker 1: is there's a very large amount of relatively low value 686 00:38:00,239 --> 00:38:05,160 Speaker 1: stuff that's quite profitable and is done on a regular basis. So, 687 00:38:05,280 --> 00:38:08,080 Speaker 1: for instance, if you want to have an MRI in Britain, 688 00:38:08,600 --> 00:38:11,600 Speaker 1: you might have to drive ways or travel in order 689 00:38:11,640 --> 00:38:13,439 Speaker 1: to get one, or you might have wait a month 690 00:38:13,520 --> 00:38:16,759 Speaker 1: or two. Whereas every doctor's office in Princeton has one 691 00:38:16,800 --> 00:38:19,640 Speaker 1: of these things. They're laying idle most of the time. 692 00:38:19,800 --> 00:38:22,319 Speaker 1: That costs a lot of money. So there's just a 693 00:38:22,320 --> 00:38:26,719 Speaker 1: lot more of those procedures being done which are helpful 694 00:38:26,880 --> 00:38:28,720 Speaker 1: but maybe not super helpful. 695 00:38:29,320 --> 00:38:35,200 Speaker 2: I really kind of fascinating. What else accounts for this 696 00:38:35,320 --> 00:38:39,600 Speaker 2: big gap? You mentioned certain things that are inexpensive. We 697 00:38:39,760 --> 00:38:43,759 Speaker 2: just passed a law here that capped insulin for I 698 00:38:43,840 --> 00:38:47,520 Speaker 2: want to say Medicaid recipients. I could be getting that wrong. 699 00:38:47,920 --> 00:38:53,239 Speaker 2: At some very moderate modest cost. I think insulin has 700 00:38:53,280 --> 00:38:55,440 Speaker 2: been off patent for decades. 701 00:38:55,680 --> 00:38:57,880 Speaker 1: It was off patent from the day it was invented. 702 00:38:58,000 --> 00:39:01,640 Speaker 1: Oh is that the inventor sold it to a hospital 703 00:39:01,680 --> 00:39:06,040 Speaker 1: in Canada for a dollar each and that was it. 704 00:39:06,360 --> 00:39:09,720 Speaker 1: They no money, no patent, no nothing, It's never been. 705 00:39:10,120 --> 00:39:13,400 Speaker 2: So how on earth does something like that become crazy 706 00:39:13,480 --> 00:39:15,440 Speaker 2: expensive in a place like the United States. 707 00:39:15,680 --> 00:39:18,440 Speaker 1: Well, because it's allowed to become crazy, pens you know, 708 00:39:18,480 --> 00:39:21,080 Speaker 1: they have different delivery systems or slightly different drugs, so 709 00:39:21,120 --> 00:39:22,799 Speaker 1: they'll tell you that drugs are a little bit better 710 00:39:22,840 --> 00:39:24,879 Speaker 1: and all the rest of it. So they can keep 711 00:39:24,960 --> 00:39:28,480 Speaker 1: rolling this out and then get patents on things that 712 00:39:28,600 --> 00:39:32,040 Speaker 1: don't change the basic thing very much. And so that happens. 713 00:39:32,080 --> 00:39:34,160 Speaker 1: And I think it's not Medicaid. I think it's anyone 714 00:39:34,239 --> 00:39:39,480 Speaker 1: on Medicare Medicare who's like anyone over sixty five, and 715 00:39:39,760 --> 00:39:43,120 Speaker 1: there's a limit on how much, And so it's pretty widespread. 716 00:39:43,840 --> 00:39:47,360 Speaker 2: Given all of this, what has led to all of 717 00:39:47,400 --> 00:39:51,880 Speaker 2: this inequality in the United States, what policies are should 718 00:39:51,960 --> 00:39:53,240 Speaker 2: we be pointing a finger at. 719 00:39:53,640 --> 00:39:58,320 Speaker 1: Well, here's something. Maybe let's just go back one second 720 00:39:58,360 --> 00:40:00,520 Speaker 1: to the because the hospital's a big part of this. 721 00:40:00,600 --> 00:40:05,040 Speaker 1: They're just unbelievably expensive and they're very luxurious compared with 722 00:40:05,120 --> 00:40:07,760 Speaker 1: hospitals in Britain. If you go into a hospital in Britain, 723 00:40:08,040 --> 00:40:10,880 Speaker 1: there might be twelve people in the ward. There's no 724 00:40:11,000 --> 00:40:13,400 Speaker 1: private rooms, for instance, and that sort of thing is 725 00:40:13,520 --> 00:40:16,200 Speaker 1: very very expensive. And maybe we're a rich country, maybe 726 00:40:16,200 --> 00:40:19,280 Speaker 1: we want to have that, but it certainly costs a lot, 727 00:40:19,480 --> 00:40:21,279 Speaker 1: and there are cheaper ways of doing that, and it 728 00:40:21,320 --> 00:40:24,680 Speaker 1: seems to have very little effect on life expectancy, and 729 00:40:24,760 --> 00:40:27,040 Speaker 1: you know it doesn't kill you as part of it. 730 00:40:27,200 --> 00:40:29,279 Speaker 1: And one other thing that's worth noting is no one 731 00:40:29,320 --> 00:40:31,480 Speaker 1: really understands that. But I think the last four or 732 00:40:31,480 --> 00:40:36,520 Speaker 1: five years has stopped growing, the total expenditure and health 733 00:40:36,719 --> 00:40:40,520 Speaker 1: has stopped growing. And there are people who were involved 734 00:40:40,520 --> 00:40:43,640 Speaker 1: in the writing of Obamacare who claim that the provisions 735 00:40:43,640 --> 00:40:46,399 Speaker 1: in Obamacare are actually kicking in, but I don't think 736 00:40:46,440 --> 00:40:47,719 Speaker 1: anyone knows the answer to that. 737 00:40:47,960 --> 00:40:51,160 Speaker 2: I'm going to tell you my single biggest observation about 738 00:40:51,800 --> 00:40:56,400 Speaker 2: the ACA and Obamacare is as soon as that became 739 00:40:56,440 --> 00:41:01,960 Speaker 2: a law of land, which is what was that two eleven. 740 00:41:02,360 --> 00:41:04,640 Speaker 1: It was the law earlier, but it didn't kick in 741 00:41:04,719 --> 00:41:05,759 Speaker 1: for a couple of years. 742 00:41:06,040 --> 00:41:10,000 Speaker 2: All of these walking clinics popped up everywhere where you 743 00:41:10,000 --> 00:41:12,480 Speaker 2: didn't have to go to your regular physician, and you 744 00:41:12,520 --> 00:41:14,759 Speaker 2: didn't have to go to the emergency room. You could 745 00:41:14,760 --> 00:41:18,719 Speaker 2: walk in, show an insurance card, they would diagnose you 746 00:41:18,760 --> 00:41:21,839 Speaker 2: for something. Half the time it's an antibiotic, and they 747 00:41:21,840 --> 00:41:26,000 Speaker 2: send you on your way. And those are everywhere, especially 748 00:41:26,440 --> 00:41:31,280 Speaker 2: in cities that were kind of medical deserts for a while. 749 00:41:31,560 --> 00:41:34,239 Speaker 2: I'm curious what the impact of that might have been. 750 00:41:34,360 --> 00:41:36,480 Speaker 1: Some of them are very cheap. They don't do very 751 00:41:36,600 --> 00:41:38,719 Speaker 1: much most of them, and a lot of people go 752 00:41:38,760 --> 00:41:41,880 Speaker 1: in there wanting an antibiotic, but they've got flu and 753 00:41:42,000 --> 00:41:47,000 Speaker 1: it's a virus. They say, you can't do that. So 754 00:41:47,520 --> 00:41:49,520 Speaker 1: I've gone in there to try and get things, and 755 00:41:49,600 --> 00:41:51,920 Speaker 1: you know, I didn't get what I wanted. To go 756 00:41:52,040 --> 00:41:55,600 Speaker 1: somewhere else. But I think there are things like that 757 00:41:55,920 --> 00:41:58,839 Speaker 1: which are helping control costs. But I'm now out of 758 00:41:58,880 --> 00:42:03,239 Speaker 1: my zone of expertise here, But I mean, the one 759 00:42:03,280 --> 00:42:05,759 Speaker 1: thing that Anna and I spent a lot of time 760 00:42:05,760 --> 00:42:09,440 Speaker 1: writing about in our book was that if you have 761 00:42:09,600 --> 00:42:14,000 Speaker 1: insurance through your employer, right, that cost nowadays about eleven 762 00:42:14,080 --> 00:42:18,440 Speaker 1: thousand dollars a year per employee and about twenty thousand 763 00:42:18,520 --> 00:42:22,520 Speaker 1: dollars for a family policy. That costs about the same 764 00:42:22,680 --> 00:42:26,480 Speaker 1: for the CEO as it does for the CEO's driver, right, 765 00:42:26,760 --> 00:42:30,920 Speaker 1: because you're ensuring the body, not the salary, right, Right. 766 00:42:31,160 --> 00:42:34,800 Speaker 1: So this puts an enormous burden on low wage workers, 767 00:42:35,440 --> 00:42:41,080 Speaker 1: and it's been a big contributor to outsourcing jobs, so 768 00:42:41,120 --> 00:42:46,200 Speaker 1: that most companies don't hire their own security, their elevator operators, 769 00:42:46,280 --> 00:42:50,759 Speaker 1: they're transport people their you know, food service people and 770 00:42:50,760 --> 00:42:52,919 Speaker 1: all the rest of it, and a lot of good 771 00:42:53,000 --> 00:42:55,640 Speaker 1: jobs have been lost because of that. So that's one 772 00:42:55,719 --> 00:42:59,000 Speaker 1: of the ways in which this very expensive healthcare is 773 00:42:59,080 --> 00:43:00,920 Speaker 1: eating the harm of our economy. 774 00:43:01,080 --> 00:43:05,479 Speaker 2: Huh. So, in other words, people, companies, employers don't want 775 00:43:05,480 --> 00:43:10,640 Speaker 2: to hire a forty thousand dollars employee right still far 776 00:43:10,719 --> 00:43:14,319 Speaker 2: above minimum wage, but on the bottom half of the 777 00:43:14,320 --> 00:43:20,000 Speaker 2: wage spectrum, because there's an eleven thousand dollars right tag 778 00:43:20,120 --> 00:43:21,440 Speaker 2: on top of that for healthcare. 779 00:43:21,640 --> 00:43:25,200 Speaker 1: One CEO told us that their HR people came run 780 00:43:25,200 --> 00:43:28,040 Speaker 1: into the annual conference where they were looking ahead for 781 00:43:28,080 --> 00:43:30,319 Speaker 1: the pricing and a lots of it, and he said, 782 00:43:30,320 --> 00:43:33,160 Speaker 1: we have bad news for you that your health care 783 00:43:33,239 --> 00:43:37,200 Speaker 1: costs the policies you have are going to cost forty percent. 784 00:43:36,920 --> 00:43:38,719 Speaker 2: More forty forty zero. 785 00:43:38,840 --> 00:43:42,120 Speaker 1: It was only one year, but as you said, these 786 00:43:42,120 --> 00:43:43,839 Speaker 1: things are going up like crazy. 787 00:43:43,760 --> 00:43:46,239 Speaker 2: Nine percent a year for yeah, again, three or. 788 00:43:46,239 --> 00:43:48,680 Speaker 1: Four years and it can be forty percent. So there's 789 00:43:48,760 --> 00:43:51,920 Speaker 1: this sort of thing. And so the company said, you 790 00:43:51,920 --> 00:43:54,400 Speaker 1: know that we can't do that, it's not going to happen, 791 00:43:55,000 --> 00:43:57,279 Speaker 1: and what should we do? And they said, you get 792 00:43:57,360 --> 00:43:59,360 Speaker 1: McKenzie and you fire all your low paid. 793 00:43:59,239 --> 00:44:04,920 Speaker 2: Staff really and then hire them back through some company 794 00:44:04,960 --> 00:44:06,480 Speaker 2: that is gonna. 795 00:44:06,280 --> 00:44:10,680 Speaker 1: The ramjam cleaning company, you know, a wheels driving company, 796 00:44:11,160 --> 00:44:14,120 Speaker 1: and you know this CEO at least, and I have 797 00:44:14,120 --> 00:44:16,799 Speaker 1: no way of verifying this thought that many of these 798 00:44:16,840 --> 00:44:19,640 Speaker 1: workers were undocumented, ah. 799 00:44:19,280 --> 00:44:21,960 Speaker 2: Alien, so they would never get hired anywhere else anyway. 800 00:44:22,400 --> 00:44:25,920 Speaker 1: Well, there's an informal economy. Yeah, but they're probably not 801 00:44:25,920 --> 00:44:29,600 Speaker 1: getting healthcare benefits, so you've shifted the healthcare benefits out 802 00:44:29,640 --> 00:44:34,000 Speaker 1: of the company essentially. And you know it means you're 803 00:44:34,080 --> 00:44:39,759 Speaker 1: much more interested in hiring high income workers and very uninterested. 804 00:44:39,880 --> 00:44:42,520 Speaker 1: You said, as someone who's being paid thirty thousand a year, 805 00:44:42,719 --> 00:44:45,360 Speaker 1: forty thousand a year, you don't want to carry eleven 806 00:44:45,400 --> 00:44:47,280 Speaker 1: thousand dollars worth of health care insurance. 807 00:44:47,480 --> 00:44:52,160 Speaker 2: Huh. That's really quite fascinating. Let's talk about immigration. It 808 00:44:52,280 --> 00:44:56,640 Speaker 2: seems like the total numbers of legal US immigrants have 809 00:44:56,760 --> 00:45:00,680 Speaker 2: been falling over the past few decades, at least relative 810 00:45:00,760 --> 00:45:04,239 Speaker 2: to the overall labor pool. Tell us what's going on 811 00:45:04,320 --> 00:45:06,160 Speaker 2: with immigration in the United States. 812 00:45:06,440 --> 00:45:10,080 Speaker 1: I actually didn't know that, though i'd heard something yesterday which. 813 00:45:10,000 --> 00:45:12,400 Speaker 2: Well, is falling and then it's starting to tick back up. 814 00:45:12,440 --> 00:45:15,279 Speaker 2: But it's still below where we were had you just 815 00:45:15,320 --> 00:45:17,040 Speaker 2: projected it out twenty years ago. 816 00:45:17,400 --> 00:45:20,279 Speaker 1: Yeah, that could well be. No, I don't know much 817 00:45:20,320 --> 00:45:24,080 Speaker 1: about that, and you know, I am obviously a well 818 00:45:24,120 --> 00:45:28,240 Speaker 1: documented alien. I'm not an alien. I'm not an American citizen, 819 00:45:28,480 --> 00:45:30,440 Speaker 1: though it took me thirty years to get run into 820 00:45:31,440 --> 00:45:31,919 Speaker 1: doing that. 821 00:45:32,120 --> 00:45:33,440 Speaker 2: Dual passports or just one. 822 00:45:33,560 --> 00:45:35,839 Speaker 1: I have dual passports, which in Britain they allow you 823 00:45:35,880 --> 00:45:38,480 Speaker 1: to do. I would not be sir Angus if I'd 824 00:45:38,480 --> 00:45:41,359 Speaker 1: given up my b that's right passport and they check 825 00:45:41,400 --> 00:45:41,759 Speaker 1: on that. 826 00:45:42,160 --> 00:45:44,360 Speaker 2: Oh really, Well you get a phone call from the 827 00:45:44,440 --> 00:45:46,680 Speaker 2: Queen Angus, what's going on? 828 00:45:47,000 --> 00:45:50,200 Speaker 1: No? No, no, no no. But it's a very British thing. 829 00:45:51,160 --> 00:45:53,960 Speaker 1: That are secret committees that you've no idea, who are 830 00:45:54,000 --> 00:45:56,680 Speaker 1: members of those of the Great and the Good who 831 00:45:56,719 --> 00:46:00,400 Speaker 1: decide who they're going to give knighthoods to or other honors. 832 00:46:00,960 --> 00:46:03,960 Speaker 1: And I have friends who are British who have a 833 00:46:03,960 --> 00:46:06,920 Speaker 1: Nobel prize who did not get one for many, many years. 834 00:46:07,280 --> 00:46:09,600 Speaker 2: So it wasn't just the pride because you are a year 835 00:46:09,719 --> 00:46:14,840 Speaker 2: later got the knighthood, that's right. What was that call like? 836 00:46:14,880 --> 00:46:17,040 Speaker 2: As long as we're talking about it, well, it. 837 00:46:16,960 --> 00:46:19,800 Speaker 1: Doesn't come from the Queen or even from the Prime Minister, 838 00:46:19,960 --> 00:46:23,960 Speaker 1: but it does come from the British Consulate here in 839 00:46:24,040 --> 00:46:27,400 Speaker 1: New York City and say would you accept a knighthood 840 00:46:27,440 --> 00:46:29,960 Speaker 1: if it was bestowed on you? And I said, well, 841 00:46:30,000 --> 00:46:30,560 Speaker 1: are you kidding? 842 00:46:30,600 --> 00:46:32,799 Speaker 2: Of course, of course you have to go fly back 843 00:46:32,840 --> 00:46:33,640 Speaker 2: to London for this. 844 00:46:33,760 --> 00:46:36,080 Speaker 1: Well, there's actually a bunch of places you could go. 845 00:46:36,320 --> 00:46:38,640 Speaker 1: I could do what Sean Connery did and insist that 846 00:46:38,640 --> 00:46:40,799 Speaker 1: it'd be given to me in Scotland, which is where 847 00:46:40,840 --> 00:46:44,959 Speaker 1: I grew up, at Holyrood Palace. But there's a whole 848 00:46:44,960 --> 00:46:48,520 Speaker 1: bunch of dates over the years, and it's an interesting 849 00:46:48,560 --> 00:46:52,239 Speaker 1: thing because the royal family always does it. They've never delegated, 850 00:46:52,360 --> 00:46:57,560 Speaker 1: even during wartime to civil servants however, elevated or anything. 851 00:46:58,040 --> 00:47:00,799 Speaker 1: So there's about four members that are all who do this, 852 00:47:01,600 --> 00:47:04,560 Speaker 1: and the Queen, you know, did very few towards the 853 00:47:04,640 --> 00:47:08,680 Speaker 1: end of her life. But you know, Charles did a lot, 854 00:47:09,239 --> 00:47:14,279 Speaker 1: Princess Anne does a lot, and William Wills does a lot. 855 00:47:14,320 --> 00:47:16,920 Speaker 1: He did me, he knew quite a lot about my 856 00:47:17,000 --> 00:47:19,480 Speaker 1: work and he hit me with the sword that was 857 00:47:19,520 --> 00:47:20,480 Speaker 1: his grandfather. 858 00:47:20,760 --> 00:47:26,000 Speaker 2: So I think it's hilarious that Sean Connery said oh, knighthood, 859 00:47:26,800 --> 00:47:29,160 Speaker 2: bring me the Queen, send the royal family to me. 860 00:47:29,480 --> 00:47:31,920 Speaker 2: I'll be right here in Scotland. Who else could have 861 00:47:32,000 --> 00:47:35,120 Speaker 2: gotten away with that? I don't know, but that's absolutely hilio. 862 00:47:35,239 --> 00:47:39,759 Speaker 2: So so let's talk a little bit about what you 863 00:47:39,800 --> 00:47:45,080 Speaker 2: see in terms of legal immigration, what's happening here in 864 00:47:45,120 --> 00:47:46,839 Speaker 2: the States and how important is it? 865 00:47:47,120 --> 00:47:51,080 Speaker 1: Yeah, okay, I mean the legal immigration is a lot 866 00:47:51,120 --> 00:47:53,239 Speaker 1: of its high end immigration. 867 00:47:53,360 --> 00:47:56,920 Speaker 2: I mean skilled, skilled people, semi wealthy. 868 00:47:57,040 --> 00:47:58,680 Speaker 1: Who are going to work for you know, and you 869 00:47:58,719 --> 00:48:01,880 Speaker 1: see the CEOs of people like Microsoft. 870 00:48:01,360 --> 00:48:04,640 Speaker 2: And so all the Silicon Valley, something like twenty five 871 00:48:04,640 --> 00:48:07,720 Speaker 2: percent of the c suite, maybe even more. We're not 872 00:48:07,719 --> 00:48:08,200 Speaker 2: not born in. 873 00:48:08,160 --> 00:48:10,359 Speaker 1: The United We're not born in the United States, right, 874 00:48:10,640 --> 00:48:15,719 Speaker 1: And there's also long literature of creativity and immigrants, so 875 00:48:15,800 --> 00:48:19,480 Speaker 1: that many of immigrants in the United States Tesla not 876 00:48:20,239 --> 00:48:22,400 Speaker 1: Elon Musk, but Elon Musk of course was born in 877 00:48:22,440 --> 00:48:27,920 Speaker 1: South Africa. Yeah, we're immigrants. And there's some suggestion immigrants 878 00:48:27,920 --> 00:48:33,960 Speaker 1: are much healthier than non immigrants, and that's partly because 879 00:48:34,000 --> 00:48:36,799 Speaker 1: immigrants are sort of selected special people. 880 00:48:36,640 --> 00:48:38,680 Speaker 2: Self selecting. You're going to pick up and move halfway 881 00:48:38,719 --> 00:48:41,640 Speaker 2: around the world. Yeah, you have to be motivated. You 882 00:48:41,719 --> 00:48:44,200 Speaker 2: have to be fairly robust to do that, and you 883 00:48:44,239 --> 00:48:48,120 Speaker 2: have to have a certain type of mental attitude and constitution, 884 00:48:48,239 --> 00:48:49,120 Speaker 2: I would imagine. 885 00:48:49,160 --> 00:48:51,600 Speaker 1: I think that's right. But of course the big controversy 886 00:48:51,640 --> 00:48:55,600 Speaker 1: nowadays is not about that end of things. It's about 887 00:48:55,680 --> 00:48:56,200 Speaker 1: the other. 888 00:48:56,160 --> 00:48:58,520 Speaker 2: End, illegal immigration, well, or. 889 00:48:59,000 --> 00:49:03,680 Speaker 1: The less skilled undocumented aliens who are swarming across the 890 00:49:03,680 --> 00:49:07,680 Speaker 1: border in large numbers, and we have no mechanism for 891 00:49:07,800 --> 00:49:10,080 Speaker 1: stopping that. So I don't want to talk about that 892 00:49:10,320 --> 00:49:12,960 Speaker 1: because that's not my area of expertise, and you hear 893 00:49:12,960 --> 00:49:15,799 Speaker 1: about it in the newspapers and on the radio and 894 00:49:15,840 --> 00:49:18,960 Speaker 1: television all the time. But just about this question as 895 00:49:19,040 --> 00:49:26,040 Speaker 1: to whether immigration lowers the wages of Native Americans now, 896 00:49:26,160 --> 00:49:29,800 Speaker 1: David Carr is one of the big authors who claims 897 00:49:29,800 --> 00:49:33,520 Speaker 1: it doesn't have any such effect as the toll. Paul Krugman, 898 00:49:33,600 --> 00:49:36,440 Speaker 1: who you've talked about, has been writing blistering pieces in 899 00:49:36,440 --> 00:49:39,200 Speaker 1: the New York Times saying it doesn't decrease local wages, 900 00:49:39,800 --> 00:49:43,920 Speaker 1: denouncing the lump fallacy, which says that there's only finite 901 00:49:43,960 --> 00:49:46,640 Speaker 1: number of jobs in America and if immigrants get them, 902 00:49:47,000 --> 00:49:49,520 Speaker 1: there's none left, or there's fewer left for ordinary people, 903 00:49:49,840 --> 00:49:51,880 Speaker 1: and I suspect that's not true. I think we've been 904 00:49:51,880 --> 00:49:54,280 Speaker 1: getting this wrong actually, and really I think it does 905 00:49:54,600 --> 00:49:57,120 Speaker 1: in fact, and so I think one of the reasons 906 00:49:57,120 --> 00:50:01,400 Speaker 1: that inequality is so high now is because fifteen percent 907 00:50:01,440 --> 00:50:05,360 Speaker 1: of the population is foreign born, which was also true 908 00:50:05,560 --> 00:50:09,879 Speaker 1: during the Gilded Age, and we had this huge dip. 909 00:50:09,920 --> 00:50:11,680 Speaker 1: I don't know if you've seen these pictures, but if 910 00:50:11,719 --> 00:50:13,960 Speaker 1: you go back to eighteen ninety, but fifteen percent of 911 00:50:14,000 --> 00:50:16,919 Speaker 1: the population was foreign born. If you look at it now, 912 00:50:17,000 --> 00:50:20,799 Speaker 1: fifteen percent is foreign born. And in the trough in 913 00:50:20,840 --> 00:50:23,920 Speaker 1: the late sixties it was down to I don't know, 914 00:50:24,040 --> 00:50:25,000 Speaker 1: seven or eight percent. 915 00:50:25,719 --> 00:50:28,200 Speaker 2: Post war era is that it dropped in half. 916 00:50:28,719 --> 00:50:32,279 Speaker 1: Yeah, Well, what happened was the laws the banning of 917 00:50:32,320 --> 00:50:36,000 Speaker 1: immigrants making it almost impossible were in the twenties, so 918 00:50:36,040 --> 00:50:39,480 Speaker 1: it took a long time to come down. And then 919 00:50:39,600 --> 00:50:43,520 Speaker 1: there was this Heart Cellar Act which was passed in 920 00:50:43,560 --> 00:50:47,319 Speaker 1: I think nineteen sixty eight, and it was passed under 921 00:50:47,360 --> 00:50:50,320 Speaker 1: the promise that there would be no increase in immigration 922 00:50:50,440 --> 00:50:54,200 Speaker 1: at all, and that turned out to be completely false. 923 00:50:55,040 --> 00:50:57,200 Speaker 1: And it was completely false because they weren't counting the 924 00:50:57,239 --> 00:51:01,239 Speaker 1: family members who were allowed to come in afterwards, and 925 00:51:01,280 --> 00:51:03,760 Speaker 1: that's what's driven the huge increase. 926 00:51:03,840 --> 00:51:06,279 Speaker 2: Back to fifteen percent what we saw, or go. 927 00:51:06,400 --> 00:51:08,600 Speaker 1: Back to fifteen percent, And if you look at income 928 00:51:08,640 --> 00:51:11,399 Speaker 1: inequality in America it looks exactly like that too. 929 00:51:11,680 --> 00:51:15,960 Speaker 2: So so that leads to the obvious question, how parallel 930 00:51:16,320 --> 00:51:22,480 Speaker 2: is or what is there a mechanism between immigration and inequality? 931 00:51:22,719 --> 00:51:25,560 Speaker 1: Yes, I think so, though I'm now out on a 932 00:51:25,600 --> 00:51:27,960 Speaker 1: limb and lots of my economist friends are going to 933 00:51:28,000 --> 00:51:30,200 Speaker 1: denounce me and Paul Krugman and that is probably going 934 00:51:30,239 --> 00:51:32,240 Speaker 1: to beat me over the head with a chair or something. 935 00:51:32,280 --> 00:51:34,719 Speaker 1: But even in that, you know. 936 00:51:34,719 --> 00:51:37,759 Speaker 2: David Lee, by the way, he's a very genteel. 937 00:51:37,400 --> 00:51:41,000 Speaker 1: I know, I know, Paul. It's not like debating Larry Summers, 938 00:51:41,040 --> 00:51:42,080 Speaker 1: which I did recently. 939 00:51:42,520 --> 00:51:43,480 Speaker 2: Oh I'm so sorry. 940 00:51:43,600 --> 00:51:47,520 Speaker 1: Yeah, but you should watch the video as a video. 941 00:51:47,560 --> 00:51:49,920 Speaker 2: Oh really, I'll link to it in there. 942 00:51:49,760 --> 00:51:53,359 Speaker 1: Which it was a very unpleasant unkinnter. But he took 943 00:51:53,440 --> 00:51:58,600 Speaker 1: great objection to this book. So I think it is 944 00:51:58,640 --> 00:52:01,719 Speaker 1: true that once happened, if you bring in large numbers 945 00:52:02,040 --> 00:52:07,160 Speaker 1: of unskilled immigrants, then that is good for rich people 946 00:52:07,600 --> 00:52:11,080 Speaker 1: because it provides and it's good for employers and provides 947 00:52:11,320 --> 00:52:15,319 Speaker 1: a very large, very cheap labor force pool of low 948 00:52:15,400 --> 00:52:18,400 Speaker 1: wage workers who work in agriculture, who work you know, 949 00:52:18,440 --> 00:52:20,839 Speaker 1: if you go to Princeton, New Jersey and walk around town, 950 00:52:21,160 --> 00:52:24,480 Speaker 1: they are all these beautifully maintained houses covered with velvet 951 00:52:24,480 --> 00:52:29,320 Speaker 1: green lawns, you know, and everything is immaculately maintained. Well. 952 00:52:30,000 --> 00:52:33,760 Speaker 1: I don't think anyone who you would see doing that work. 953 00:52:35,000 --> 00:52:36,360 Speaker 1: You would hear them speaking English. 954 00:52:36,560 --> 00:52:40,480 Speaker 2: All farm born. They're all foreign so at least the 955 00:52:40,560 --> 00:52:45,040 Speaker 2: children of farm board I've noticed. So it's landscapers, it's 956 00:52:45,160 --> 00:52:50,560 Speaker 2: farm workers. During the financial the building boom leading up 957 00:52:50,600 --> 00:52:59,680 Speaker 2: to the financial crisis, the it was commonly understood that painters, framers, stonemason, 958 00:52:59,760 --> 00:53:04,800 Speaker 2: roof plumbers, electric like a huge influx of people from 959 00:53:05,320 --> 00:53:09,440 Speaker 2: Mexico and South America who were skilled workers. These aren't 960 00:53:09,520 --> 00:53:12,719 Speaker 2: unskilled workers, and they paid they were paid a pretty 961 00:53:12,800 --> 00:53:17,160 Speaker 2: decent wage for building houses. You still see, that's a 962 00:53:17,239 --> 00:53:21,720 Speaker 2: pretty substantial slice. And when people complain they can't find 963 00:53:21,760 --> 00:53:25,560 Speaker 2: farm workers or they can't find roofers, it's because they're 964 00:53:25,680 --> 00:53:29,839 Speaker 2: very often it's because there's been some shift in who 965 00:53:29,920 --> 00:53:33,480 Speaker 2: is working where, who was staying where. Right, Again, all anecdotal, 966 00:53:33,600 --> 00:53:36,720 Speaker 2: not hard data, but it's just if you look. 967 00:53:36,600 --> 00:53:39,520 Speaker 1: At these inequality patterns in the Gilded Age when you 968 00:53:39,520 --> 00:53:42,520 Speaker 1: had these huge houses and many servants and all the 969 00:53:42,560 --> 00:53:45,160 Speaker 1: rest of it. Now we don't have domestic servants, but 970 00:53:45,200 --> 00:53:48,200 Speaker 1: we do have people who do the same things. We 971 00:53:48,320 --> 00:53:51,480 Speaker 1: look after our yards and to look after it. And 972 00:53:51,560 --> 00:53:54,480 Speaker 1: you know, if you go to European countries, you just 973 00:53:54,520 --> 00:53:56,360 Speaker 1: don't see that. I mean, I remember talking to some 974 00:53:56,480 --> 00:53:58,239 Speaker 1: Danish friends and they say they can't afford to have 975 00:53:58,280 --> 00:54:01,520 Speaker 1: the roof on their house replaced because you know, relative 976 00:54:01,560 --> 00:54:03,920 Speaker 1: to their salaries, it costs four or five times what 977 00:54:03,960 --> 00:54:05,160 Speaker 1: it would cost in prinsident. 978 00:54:05,480 --> 00:54:08,520 Speaker 2: Really. Yeah, so we pay more for health care but 979 00:54:08,800 --> 00:54:13,040 Speaker 2: less for landscaping and contract absolutely. Huh. That's really fascinating. 980 00:54:13,239 --> 00:54:18,320 Speaker 2: So what other factors are driving inequality? When it comes 981 00:54:18,360 --> 00:54:23,640 Speaker 2: to immigration, I have like a very distorted perspective because 982 00:54:23,760 --> 00:54:27,440 Speaker 2: I think of the people like yourself or Silicon Valley 983 00:54:27,880 --> 00:54:31,600 Speaker 2: or Elon Musk coming into the United States either starting 984 00:54:31,640 --> 00:54:36,560 Speaker 2: businesses or bringing over a highly regarded stem we call 985 00:54:36,600 --> 00:54:42,480 Speaker 2: it skill set, science, technology, engineering, and math. Is that 986 00:54:42,760 --> 00:54:45,759 Speaker 2: who's coming over as legal immigrants? Or is that sort 987 00:54:45,800 --> 00:54:48,480 Speaker 2: of a distorted perspective? 988 00:54:48,520 --> 00:54:52,120 Speaker 1: And legal immigrants You've got both because a lot of 989 00:54:52,160 --> 00:54:55,000 Speaker 1: them are families of unskilled people, not particularly skilled. But 990 00:54:55,040 --> 00:54:57,960 Speaker 1: you also compared with the general population, where you think 991 00:54:58,000 --> 00:55:01,319 Speaker 1: it would probably be a normal curve with skills in 992 00:55:01,360 --> 00:55:04,759 Speaker 1: the middle. Immigrants, I think in almost all countries are 993 00:55:04,880 --> 00:55:09,200 Speaker 1: more bimodal. H Yes, you've got these very skilled people 994 00:55:09,560 --> 00:55:14,040 Speaker 1: places like Australia. And someone told me the other day 995 00:55:14,040 --> 00:55:18,040 Speaker 1: that sheriff immigrants foreign born in Australia is over thirty percent. 996 00:55:18,320 --> 00:55:19,319 Speaker 2: That wouldn't surprise me. 997 00:55:19,360 --> 00:55:22,840 Speaker 1: And they would like more. And that's because they have 998 00:55:22,880 --> 00:55:25,280 Speaker 1: an income test or they have a wealth test or whatever. 999 00:55:25,480 --> 00:55:29,000 Speaker 2: Oh really, yes, And where are those immigrants coming from. 1000 00:55:29,040 --> 00:55:32,359 Speaker 2: Are they coming from the Philippines and Vietnam or are 1001 00:55:32,400 --> 00:55:33,840 Speaker 2: they coming from elsewhere? 1002 00:55:34,040 --> 00:55:37,600 Speaker 1: Many places, I think. I mean they're very you know, 1003 00:55:37,719 --> 00:55:42,000 Speaker 1: strong Serbian Greek communities, but also a lot of them 1004 00:55:42,040 --> 00:55:43,719 Speaker 1: from East Asia nowadays. 1005 00:55:44,000 --> 00:55:45,920 Speaker 2: Pretty good for a penal colony, right. 1006 00:55:45,800 --> 00:55:47,640 Speaker 1: Pretty good for a penal colony. You know, they call 1007 00:55:47,719 --> 00:55:50,240 Speaker 1: the latest the new immigrants, they call them boat people, 1008 00:55:50,920 --> 00:55:52,680 Speaker 1: and that's the first thing they do when they get 1009 00:55:52,719 --> 00:55:53,959 Speaker 1: to Australia is buy a bone. 1010 00:55:54,080 --> 00:55:56,919 Speaker 2: That's very funny because when we talk about both people 1011 00:55:56,920 --> 00:56:00,440 Speaker 2: in the United States, they're coming over from Cuban elsewhere 1012 00:56:00,480 --> 00:56:05,360 Speaker 2: on a boat, not buying a boat. That's really fascinating. 1013 00:56:05,480 --> 00:56:10,239 Speaker 2: So we haven't really talked about education very much other 1014 00:56:10,320 --> 00:56:15,640 Speaker 2: other than the whole PC thing. How significant is education 1015 00:56:16,080 --> 00:56:22,839 Speaker 2: to inequality, whether it's on the immigrant side or domestically 1016 00:56:23,360 --> 00:56:24,120 Speaker 2: born and raised. 1017 00:56:24,320 --> 00:56:28,560 Speaker 1: Okay, so let me go back to not income inequality 1018 00:56:28,600 --> 00:56:33,000 Speaker 1: against so much, but this education inequality because I think 1019 00:56:33,160 --> 00:56:38,000 Speaker 1: this distinction that is so important here between people who 1020 00:56:38,000 --> 00:56:41,080 Speaker 1: have a four year college degree and people who do not, 1021 00:56:41,960 --> 00:56:45,239 Speaker 1: that inequality is threatening to bring us down. I think 1022 00:56:45,280 --> 00:56:46,240 Speaker 1: that's the most serious. 1023 00:56:46,440 --> 00:56:52,080 Speaker 2: So before we get to college, there is a relatively 1024 00:56:52,120 --> 00:56:56,080 Speaker 2: small group of people who aren't even high school graduates. 1025 00:56:56,440 --> 00:56:58,280 Speaker 1: But that's the client over tirement. 1026 00:56:58,280 --> 00:57:01,319 Speaker 2: That's faded to a very small percentage. 1027 00:57:01,480 --> 00:57:04,200 Speaker 1: About what third of the population has a four year 1028 00:57:04,280 --> 00:57:07,600 Speaker 1: BA or more about a third of the population has 1029 00:57:07,680 --> 00:57:11,480 Speaker 1: some college, which means they went to So it's two 1030 00:57:11,480 --> 00:57:14,960 Speaker 1: thirds no some college, but some college include a two 1031 00:57:15,040 --> 00:57:16,000 Speaker 1: year no. 1032 00:57:16,040 --> 00:57:18,000 Speaker 2: I mean there's a third with a college degree, and 1033 00:57:18,040 --> 00:57:21,400 Speaker 2: then another an additional third with some college meaning they 1034 00:57:21,400 --> 00:57:22,880 Speaker 2: have a high school degree. 1035 00:57:23,080 --> 00:57:26,640 Speaker 1: No, they have a high school degree, but they also 1036 00:57:26,800 --> 00:57:31,240 Speaker 1: have maybe a whatever the thing that you get from 1037 00:57:31,280 --> 00:57:31,960 Speaker 1: a junior. 1038 00:57:31,720 --> 00:57:33,600 Speaker 2: College ged the equivalent degree. 1039 00:57:33,680 --> 00:57:36,400 Speaker 1: No, no, no, g d's equivalent for high school. This 1040 00:57:36,480 --> 00:57:41,439 Speaker 1: is oh, the community college. It's called an associates agree 1041 00:57:41,640 --> 00:57:44,960 Speaker 1: or something, or they've been to college but didn't finish. Right, 1042 00:57:45,360 --> 00:57:47,960 Speaker 1: So the people with a two year degree and being 1043 00:57:48,000 --> 00:57:50,680 Speaker 1: to college but didn't finish or another third got it, 1044 00:57:50,760 --> 00:57:53,840 Speaker 1: and then there's a third who have high school or less. 1045 00:57:54,520 --> 00:57:56,560 Speaker 1: And the people who didn't graduate from high school are 1046 00:57:56,600 --> 00:57:57,720 Speaker 1: not all that many anymore. 1047 00:57:57,760 --> 00:58:01,440 Speaker 2: It's becoming a small So let's bring this back to college. 1048 00:58:02,080 --> 00:58:05,560 Speaker 2: How significant I assume a college degree is very significant, 1049 00:58:06,000 --> 00:58:08,080 Speaker 2: or even a two year degree is significant to your 1050 00:58:08,240 --> 00:58:13,440 Speaker 2: future earnings and your standard of living. How why does 1051 00:58:13,480 --> 00:58:13,920 Speaker 2: that gap? 1052 00:58:14,040 --> 00:58:15,960 Speaker 1: Well, the gap is enormous. If you look at the 1053 00:58:15,960 --> 00:58:18,640 Speaker 1: wages we used to You know, when I first came 1054 00:58:18,680 --> 00:58:21,680 Speaker 1: to Princeton, what you were handed out with the ration 1055 00:58:22,000 --> 00:58:25,480 Speaker 1: was that a BA bought you a forty percent premium. 1056 00:58:25,040 --> 00:58:26,520 Speaker 2: And your wage that much. 1057 00:58:27,440 --> 00:58:28,560 Speaker 1: It's now over one hundred. 1058 00:58:29,040 --> 00:58:32,440 Speaker 2: Get out of here, double, it's double. That's amazing. 1059 00:58:32,800 --> 00:58:35,720 Speaker 1: So not only that, but those are the people who 1060 00:58:35,720 --> 00:58:39,640 Speaker 1: are not getting fired from their jobs because the rising 1061 00:58:39,680 --> 00:58:43,960 Speaker 1: healthcare costs. Whereas the people that degree or not and 1062 00:58:44,200 --> 00:58:47,320 Speaker 1: what had really changed my mind about it, you know, 1063 00:58:47,360 --> 00:58:50,520 Speaker 1: and this happened to me very late in life after 1064 00:58:50,720 --> 00:58:54,919 Speaker 1: with it about pride, was this realization that when Anne 1065 00:58:54,960 --> 00:58:57,880 Speaker 1: and I were working on these people who were dying. 1066 00:58:57,640 --> 00:58:59,320 Speaker 2: From deaths of despair, that's of. 1067 00:58:59,320 --> 00:59:04,200 Speaker 1: Despair from opioid overdoses, from suicide, from alcoholism, that those 1068 00:59:04,760 --> 00:59:08,600 Speaker 1: that huge increase which started, you know, in the late 1069 00:59:08,720 --> 00:59:13,240 Speaker 1: nineties and goes on rising today, that's all among people 1070 00:59:13,280 --> 00:59:17,439 Speaker 1: without a BA. So you've got a BA, you've got 1071 00:59:17,440 --> 00:59:19,560 Speaker 1: a vaccine against these things. 1072 00:59:19,240 --> 00:59:26,160 Speaker 2: That's amazing. I vividly recalled during the pandemic lockdown, if 1073 00:59:26,200 --> 00:59:29,480 Speaker 2: you had a college degree and you're working in what 1074 00:59:29,520 --> 00:59:32,880 Speaker 2: we think of as a white collar job, you could 1075 00:59:32,920 --> 00:59:35,720 Speaker 2: work remote. Your job was pretty safe, and if you 1076 00:59:35,760 --> 00:59:39,400 Speaker 2: didn't have a college degree, you were up for grabs. 1077 00:59:39,720 --> 00:59:41,840 Speaker 1: If you look at the data, and then we have 1078 00:59:41,880 --> 00:59:45,680 Speaker 1: a recent paper that's coming out at Brookings, if you 1079 00:59:45,720 --> 00:59:48,200 Speaker 1: look at what happened during COVID, the people with a 1080 00:59:48,240 --> 00:59:51,160 Speaker 1: college degree had a slight drop in life expectancy, maybe 1081 00:59:51,280 --> 00:59:53,720 Speaker 1: half a year. But if you didn't have a four 1082 00:59:53,800 --> 00:59:57,400 Speaker 1: year degree, it's huge drops. It really got hit. 1083 00:59:57,680 --> 01:00:00,160 Speaker 2: So not just income but life expectance. 1084 01:00:00,000 --> 01:00:02,480 Speaker 1: Expectance yeah, income, I don't care about so much, you know, 1085 01:00:02,520 --> 01:00:03,760 Speaker 1: because if you're. 1086 01:00:03,600 --> 01:00:05,360 Speaker 2: Dead doesn't really matter. 1087 01:00:05,360 --> 01:00:09,160 Speaker 1: It doesn't really matter. And this is a terrible inequality 1088 01:00:09,240 --> 01:00:11,800 Speaker 1: because you know, this third of it's only a third 1089 01:00:11,800 --> 01:00:14,080 Speaker 1: of the population. I have a four year college degree 1090 01:00:14,360 --> 01:00:17,200 Speaker 1: and they're doing great. Their life expectancy continues to go 1091 01:00:17,280 --> 01:00:19,720 Speaker 1: up at least until the pandemic, and then only fell 1092 01:00:19,720 --> 01:00:22,720 Speaker 1: a little during the pandemic. But if you don't have that, 1093 01:00:23,000 --> 01:00:26,320 Speaker 1: your life expectance had been falling since nineteen twenty ten. 1094 01:00:27,240 --> 01:00:28,760 Speaker 2: Really, yes, that's amazing. 1095 01:00:28,760 --> 01:00:31,240 Speaker 1: I mean, it's just awful. And this gap in nineteen 1096 01:00:31,280 --> 01:00:33,680 Speaker 1: ninety two and life experiences about two years, it's not 1097 01:00:33,720 --> 01:00:34,840 Speaker 1: like thirteen years. 1098 01:00:35,560 --> 01:00:39,080 Speaker 2: And this is driven by the opioid crisis and the 1099 01:00:39,120 --> 01:00:42,760 Speaker 2: tendency for people without education are just much more likely 1100 01:00:43,280 --> 01:00:45,120 Speaker 2: to find themselves on the wrong end of that. 1101 01:00:45,680 --> 01:00:49,320 Speaker 1: It's not just the opioid crisis. The opioid is very important. 1102 01:00:50,000 --> 01:00:53,439 Speaker 1: Suicides are probably important, and suicide just a horrible thing, 1103 01:00:53,960 --> 01:00:57,720 Speaker 1: you know. The suicide researchers have believed since the nineteenth 1104 01:00:57,760 --> 01:01:01,680 Speaker 1: century that more educated people more likely to commit suicide. 1105 01:01:01,840 --> 01:01:04,760 Speaker 1: Is that true? It was true for many years. It's 1106 01:01:04,800 --> 01:01:06,040 Speaker 1: not true in the US anymore. 1107 01:01:06,040 --> 01:01:07,160 Speaker 2: It's flip and. 1108 01:01:07,160 --> 01:01:09,080 Speaker 1: Our suicide rate is like it used to be in 1109 01:01:09,120 --> 01:01:13,000 Speaker 1: Lithuania or in the Soviet Union before it collapsed. So 1110 01:01:13,120 --> 01:01:16,840 Speaker 1: this is to us, is a signal that there's something really, 1111 01:01:16,960 --> 01:01:20,560 Speaker 1: really wrong. But the fallen life experiencing a lot of 1112 01:01:20,560 --> 01:01:24,160 Speaker 1: them being driven by cardiovascular disease, which is, you know, 1113 01:01:24,240 --> 01:01:27,400 Speaker 1: this drop that was falling like a stone in the 1114 01:01:27,440 --> 01:01:30,200 Speaker 1: seventies and eighties and nineties for people that to be 1115 01:01:30,360 --> 01:01:30,960 Speaker 1: it stopped. 1116 01:01:31,480 --> 01:01:36,840 Speaker 2: Huh, that's fascinating. I was looking at gun deaths earlier 1117 01:01:36,880 --> 01:01:41,000 Speaker 2: today for a different project I was working on. I 1118 01:01:41,040 --> 01:01:43,560 Speaker 2: think it's something like, I'm doing these numbers off the 1119 01:01:43,600 --> 01:01:44,920 Speaker 2: top of my head, so I'm going to get it wrong. 1120 01:01:45,240 --> 01:01:48,240 Speaker 2: I think there's something like forty thousand automobile deaths a 1121 01:01:48,360 --> 01:01:52,560 Speaker 2: year in the United States, a slightly higher number of 1122 01:01:52,760 --> 01:01:56,400 Speaker 2: gun related deaths, of which something like two thirds or 1123 01:01:56,440 --> 01:02:00,000 Speaker 2: three quarters or suicides does sound about right. 1124 01:02:00,400 --> 01:02:02,640 Speaker 1: I don't know that number, but I know that the 1125 01:02:02,720 --> 01:02:06,120 Speaker 1: suicide rate is running at about forty thousand Americans a year, 1126 01:02:06,240 --> 01:02:10,000 Speaker 1: oh so, and much of that is guns, at least 1127 01:02:10,040 --> 01:02:14,680 Speaker 1: by men. Women tend not to shoot themselves. They take 1128 01:02:14,760 --> 01:02:17,000 Speaker 1: poison or suffocatable. 1129 01:02:16,360 --> 01:02:19,400 Speaker 2: The numbers are really quite astonishing. How does the US 1130 01:02:20,000 --> 01:02:24,080 Speaker 2: compare to other developed, modern wealthy. 1131 01:02:23,680 --> 01:02:25,920 Speaker 1: Countries incredibly badly? 1132 01:02:26,440 --> 01:02:26,840 Speaker 2: Really? 1133 01:02:26,960 --> 01:02:30,640 Speaker 1: Well, you know, first of all, the US is the 1134 01:02:30,720 --> 01:02:34,920 Speaker 1: only country that let pharma companies like Purdue Pharma poison 1135 01:02:34,960 --> 01:02:38,920 Speaker 1: the population. It just doesn't happen in other countries because 1136 01:02:38,920 --> 01:02:42,160 Speaker 1: that's not allowed. And you know, Perdue Pharma was paying 1137 01:02:42,320 --> 01:02:46,800 Speaker 1: enormous sums of money for campaign finance for politicians. Some 1138 01:02:46,880 --> 01:02:51,520 Speaker 1: of those politicians intervene to stop Pharma being you know 1139 01:02:51,600 --> 01:02:55,040 Speaker 1: that stop that. The DEA investigating these people. There's a 1140 01:02:55,120 --> 01:02:58,920 Speaker 1: thirty minute show which is just incredibly horrible, and that happened. 1141 01:02:58,680 --> 01:03:00,919 Speaker 2: To be fair, they made them take their name off 1142 01:03:00,960 --> 01:03:04,720 Speaker 2: of a wing of a museum. So now they've certainly 1143 01:03:04,840 --> 01:03:09,160 Speaker 2: learned their lesson. Yeah, absolutely, And in fact, the settlement, 1144 01:03:09,200 --> 01:03:11,560 Speaker 2: which costs eight or ten or twelve, but some ungodly 1145 01:03:11,600 --> 01:03:15,120 Speaker 2: amount of money, keeps getting rolled back. I don't know 1146 01:03:15,160 --> 01:03:16,280 Speaker 2: what the state is now. 1147 01:03:16,440 --> 01:03:19,080 Speaker 1: There are a lot of lawyers out there. Half the 1148 01:03:19,160 --> 01:03:21,440 Speaker 1: lawyers are working for Purdue and the other half are 1149 01:03:21,440 --> 01:03:23,120 Speaker 1: working for ex President Trump. 1150 01:03:25,440 --> 01:03:29,480 Speaker 2: Well, that's a that's a challenge. I guess it's the 1151 01:03:30,000 --> 01:03:32,760 Speaker 2: attorney full employment legislation. 1152 01:03:32,880 --> 01:03:35,160 Speaker 1: Well, except you know, the thing about the FIRMA was 1153 01:03:35,240 --> 01:03:39,680 Speaker 1: once the docs realized what they'd done right and pulled 1154 01:03:39,720 --> 01:03:42,600 Speaker 1: back and said, we're not giving you any more of that, 1155 01:03:43,440 --> 01:03:47,360 Speaker 1: the illegal drug dealers moved in. And so it's now 1156 01:03:47,520 --> 01:03:54,200 Speaker 1: a fentanyl epidemic. Fentanyl is in some sense of illegal drug. 1157 01:03:54,400 --> 01:04:00,680 Speaker 2: But it's it's poison. The number of overdose is it's 1158 01:04:00,680 --> 01:04:04,040 Speaker 2: been a line straight up going back, you know, for 1159 01:04:04,120 --> 01:04:05,360 Speaker 2: almost fifteen years now. 1160 01:04:05,440 --> 01:04:07,880 Speaker 1: Yeah, but it picked up once the doctor you know, 1161 01:04:08,040 --> 01:04:12,439 Speaker 1: so this was ignited by pharma. You know, J and Jay, 1162 01:04:12,520 --> 01:04:15,680 Speaker 1: which is one of the most you know, prize names 1163 01:04:15,680 --> 01:04:19,600 Speaker 1: in corporate America, was growing poppies and half of opium 1164 01:04:19,640 --> 01:04:23,800 Speaker 1: puppies over half of Tasmania to feed this thing. Oh really, Yes, 1165 01:04:24,280 --> 01:04:26,600 Speaker 1: that's a huge fine for that. 1166 01:04:26,680 --> 01:04:29,720 Speaker 2: And you know, you could get legal weed anywhere. I know, 1167 01:04:29,800 --> 01:04:31,400 Speaker 2: it's a different body. 1168 01:04:31,520 --> 01:04:34,000 Speaker 1: I think it's a terrible stuff, you do, Yeah, I do. 1169 01:04:34,240 --> 01:04:35,360 Speaker 1: I think it's a great mistake. 1170 01:04:35,760 --> 01:04:36,320 Speaker 2: Huh. 1171 01:04:36,360 --> 01:04:38,160 Speaker 1: And I think a lot of young people get their 1172 01:04:38,160 --> 01:04:39,160 Speaker 1: brains deformed. 1173 01:04:39,760 --> 01:04:43,240 Speaker 2: Well, you really shouldn't be smoking or eating edibles when 1174 01:04:43,240 --> 01:04:46,400 Speaker 2: you're fourteen. You're not supposed to have access to that. 1175 01:04:46,760 --> 01:04:50,520 Speaker 2: But they always had access to illegal drugs. That's the challenge. 1176 01:04:50,720 --> 01:04:53,280 Speaker 2: Do you take the money away from the illegal cartels 1177 01:04:53,280 --> 01:04:58,280 Speaker 2: who do marijuana and worse. You know, we see the 1178 01:04:58,320 --> 01:05:03,920 Speaker 2: parallels with cigarettes and alcohol. We still haven't figured this out. 1179 01:05:04,440 --> 01:05:07,480 Speaker 1: We certainly haven't figured it out. So the alcohol is 1180 01:05:07,520 --> 01:05:11,400 Speaker 1: another way of killing yourself, you know, like suicide. 1181 01:05:10,880 --> 01:05:12,520 Speaker 2: And slowly over time. 1182 01:05:12,680 --> 01:05:13,840 Speaker 1: Yeah, it just takes longer. 1183 01:05:14,040 --> 01:05:18,360 Speaker 2: Yeah, it's there's no doubt about that. So I'm kind 1184 01:05:18,360 --> 01:05:21,080 Speaker 2: of fascinating you're bringing up deaths of Despair from the 1185 01:05:21,120 --> 01:05:25,160 Speaker 2: book you wrote co wrote with your wife. When we 1186 01:05:25,280 --> 01:05:30,880 Speaker 2: look at consumer sentiment in the United States, despite lowest 1187 01:05:30,960 --> 01:05:36,320 Speaker 2: unemployment rate in fifty years, a fairly robust economy, stock 1188 01:05:36,360 --> 01:05:42,200 Speaker 2: market all time, Hyes, the consumer sentiment, especially in twenty 1189 01:05:42,240 --> 01:05:47,120 Speaker 2: twenty two, during that inflation surge, it collapsed. It was 1190 01:05:47,160 --> 01:05:50,959 Speaker 2: worse than during COVID, worse than the financial crisis, worse 1191 01:05:51,000 --> 01:05:55,200 Speaker 2: than the dot com implosion, worse than the eighty seven crash. 1192 01:05:56,040 --> 01:06:02,600 Speaker 2: Is this spate of negative consumer sentiment less related to 1193 01:06:02,680 --> 01:06:06,880 Speaker 2: inflation than perhaps all of these other things, inequality, deaths 1194 01:06:06,880 --> 01:06:12,480 Speaker 2: of despair, and a streak of hopelessness that seems to 1195 01:06:12,520 --> 01:06:14,800 Speaker 2: be at work in the bottom half of the United. 1196 01:06:14,600 --> 01:06:20,040 Speaker 1: States that's my hypothesis too. I read the book, but 1197 01:06:20,200 --> 01:06:24,240 Speaker 1: I don't have any well, except the consumer sentiment bit 1198 01:06:24,440 --> 01:06:26,840 Speaker 1: was sort of more recent than It's not really in there. 1199 01:06:27,520 --> 01:06:30,560 Speaker 1: But it drives me nuts that people say, well, you know, 1200 01:06:30,600 --> 01:06:32,800 Speaker 1: America is the most successful economy in the world, and 1201 01:06:32,800 --> 01:06:34,840 Speaker 1: if you look at all these European economies, they're doing 1202 01:06:34,920 --> 01:06:38,640 Speaker 1: terribly badly. And why don't Americans realize that? Well, one 1203 01:06:38,680 --> 01:06:42,400 Speaker 1: point two million of them died during COVID, and you 1204 01:06:42,440 --> 01:06:46,000 Speaker 1: know another two hundred thousand a year are dying from 1205 01:06:46,000 --> 01:06:49,959 Speaker 1: two hundred and fifty thousand a year are dying from alcohol, opioids, 1206 01:06:50,560 --> 01:06:53,920 Speaker 1: and suicide, and none of that is happening in any 1207 01:06:53,920 --> 01:06:55,200 Speaker 1: of these European countries. 1208 01:06:55,280 --> 01:06:58,960 Speaker 2: Oh really, the gap is that big, So clearly we. 1209 01:06:58,840 --> 01:07:01,360 Speaker 1: Need They're obviously suicides in Europe. 1210 01:07:01,280 --> 01:07:03,600 Speaker 2: Sure, but I mean one point two million is a 1211 01:07:03,680 --> 01:07:06,200 Speaker 2: low estimate. I've seen numbers as high as two million. 1212 01:07:06,640 --> 01:07:10,280 Speaker 2: Clearly we didn't do a great job during COVID. Hold 1213 01:07:10,280 --> 01:07:17,200 Speaker 2: that aside, alcohol related deaths, suicide go down the list. 1214 01:07:17,280 --> 01:07:20,480 Speaker 2: The US is far and away worse than Well. 1215 01:07:20,640 --> 01:07:22,640 Speaker 1: The right way to put this is, it's not worse 1216 01:07:22,680 --> 01:07:24,680 Speaker 1: than if you go to Lithuania, for instance, a lot 1217 01:07:24,680 --> 01:07:26,040 Speaker 1: of people died by suicide. 1218 01:07:26,080 --> 01:07:29,000 Speaker 2: But I'm not sure Lithuania is the country I want 1219 01:07:29,040 --> 01:07:32,440 Speaker 2: to con you know, to me, I look at Switzerland, 1220 01:07:32,600 --> 01:07:39,880 Speaker 2: the UK, Japan, France, Germany, Italy, those should be Australia. 1221 01:07:40,040 --> 01:07:42,640 Speaker 1: Yeah, we have to be a bit careful about levels 1222 01:07:42,680 --> 01:07:47,160 Speaker 1: and changes. So this huge upsurge since the late nineties 1223 01:07:47,320 --> 01:07:52,560 Speaker 1: in deaths of despair and to some extent in cardiovascular 1224 01:07:52,600 --> 01:07:56,240 Speaker 1: disease going the wrong way is unique. You don't see 1225 01:07:56,240 --> 01:07:58,960 Speaker 1: that rise in any other rich country. There's one other 1226 01:07:59,040 --> 01:08:02,520 Speaker 1: rich country. It's where I come from, Scotland. It has 1227 01:08:02,560 --> 01:08:04,520 Speaker 1: a drug epidemic almost as bad as the. 1228 01:08:04,560 --> 01:08:06,240 Speaker 2: Oh And where are those drugs coming from? 1229 01:08:06,280 --> 01:08:11,080 Speaker 1: If they're illegal drugs? But they're not opioids, they're metem 1230 01:08:11,120 --> 01:08:14,880 Speaker 1: tedements and things. Huh. And I don't really know enough 1231 01:08:14,920 --> 01:08:17,160 Speaker 1: about that. It's very hard to get the sort of 1232 01:08:17,280 --> 01:08:20,479 Speaker 1: data that and I would like to get, even though 1233 01:08:20,560 --> 01:08:23,200 Speaker 1: people in Scotland certainly talk to us about it. 1234 01:08:22,960 --> 01:08:27,960 Speaker 2: So why is the US seeing the cardiac deaths which 1235 01:08:28,000 --> 01:08:30,640 Speaker 2: have been improving for so long? Is this just a 1236 01:08:30,680 --> 01:08:33,920 Speaker 2: function of US obesity or what's the driver of that? 1237 01:08:34,439 --> 01:08:37,720 Speaker 1: I don't know, and I don't think anyone knows, and 1238 01:08:37,840 --> 01:08:40,720 Speaker 1: there's been The literature is not really picked up on 1239 01:08:40,760 --> 01:08:44,120 Speaker 1: the fact that it's cardiovascular mortality is going up for 1240 01:08:44,240 --> 01:08:48,920 Speaker 1: people without a degree, and it's going down for people 1241 01:08:49,240 --> 01:08:49,920 Speaker 1: with a degree. 1242 01:08:50,000 --> 01:08:51,800 Speaker 2: Oh really, so it's very bifurcated. 1243 01:08:51,880 --> 01:08:54,840 Speaker 1: Also, well, it's bifurcating too, and it may be that 1244 01:08:54,880 --> 01:08:57,720 Speaker 1: people are not taking their antique hypertensives that they used 1245 01:08:57,720 --> 01:09:01,680 Speaker 1: to obesity. It's possible, but it's a little hard to 1246 01:09:01,680 --> 01:09:04,120 Speaker 1: tell the story because if you look across different states, 1247 01:09:04,120 --> 01:09:07,799 Speaker 1: they're different to beast levels that it doesn't really seem to correlate. 1248 01:09:08,000 --> 01:09:11,360 Speaker 2: Generally speaking, if you don't have a college degree, are 1249 01:09:11,560 --> 01:09:17,959 Speaker 2: you more likely to disregard doctor's orders and not take medicine? 1250 01:09:18,000 --> 01:09:19,280 Speaker 2: Is that the implication here? 1251 01:09:20,320 --> 01:09:24,960 Speaker 1: It's possible. That's an inflammatory statement. People get very upset 1252 01:09:25,000 --> 01:09:26,760 Speaker 1: with you when you say that. It's like blaming the 1253 01:09:26,880 --> 01:09:27,960 Speaker 1: victim sort of idea. 1254 01:09:28,040 --> 01:09:30,599 Speaker 2: But it's probably trying to figure out why the victims 1255 01:09:30,600 --> 01:09:33,920 Speaker 2: are victims and there should be no stone left on time. 1256 01:09:34,040 --> 01:09:37,000 Speaker 1: Well, it also may be that it's hard to get 1257 01:09:37,080 --> 01:09:39,759 Speaker 1: in some places, it's hard to get access to doctors 1258 01:09:39,800 --> 01:09:43,080 Speaker 1: and stuff. And also, I mean, there's a positive side, 1259 01:09:43,080 --> 01:09:45,599 Speaker 1: but the gaps are still increasing, which is in cancer. 1260 01:09:45,800 --> 01:09:49,640 Speaker 1: So you know, Nixon declared war on cancer in what nineteen. 1261 01:09:49,320 --> 01:09:50,400 Speaker 2: Sixty fifty years ago. 1262 01:09:50,560 --> 01:09:54,439 Speaker 1: Nothing happened until nineteen ninety and then cancer downs have 1263 01:09:54,520 --> 01:09:57,840 Speaker 1: been falling quite rapidly, but they've been falling much more 1264 01:09:57,920 --> 01:10:01,519 Speaker 1: rapidly for people with a college degree people without. So 1265 01:10:01,560 --> 01:10:05,120 Speaker 1: for instance, breast cancer mortality for women used to be 1266 01:10:05,200 --> 01:10:10,880 Speaker 1: higher among people who were not educated, and that's the higher. Sorry, 1267 01:10:10,880 --> 01:10:13,200 Speaker 1: it used to be higher among women who were educated. 1268 01:10:14,040 --> 01:10:17,639 Speaker 1: College women had much higher mortality rates from breast cancer, 1269 01:10:17,960 --> 01:10:19,240 Speaker 1: and that's not true anymore. 1270 01:10:19,600 --> 01:10:22,600 Speaker 2: Were I kind of remember seeing something about that. Was 1271 01:10:22,640 --> 01:10:25,720 Speaker 2: it that the rates were higher or the discovery of 1272 01:10:25,800 --> 01:10:29,000 Speaker 2: that's what it was that was ultimately at fault. 1273 01:10:29,960 --> 01:10:34,840 Speaker 1: No, the discovery doesn't affect mortality. The discovery effects the 1274 01:10:34,920 --> 01:10:38,160 Speaker 1: number of years you survive after diagnosis, which is why 1275 01:10:38,200 --> 01:10:40,479 Speaker 1: we should never pay any attention to that number. Well, 1276 01:10:40,520 --> 01:10:44,800 Speaker 1: people do, but mortality rates are not affected by you know, 1277 01:10:45,160 --> 01:10:48,960 Speaker 1: well except that you might save someone's life by tacticularly. 1278 01:10:49,400 --> 01:10:53,080 Speaker 1: But the statistic that's very dubious is the one that says, 1279 01:10:53,200 --> 01:10:56,040 Speaker 1: you know, how many years you get to survive after diagnosis, 1280 01:10:56,200 --> 01:10:58,720 Speaker 1: because you could diagnose everybody with cancer at birth and 1281 01:10:58,760 --> 01:10:59,960 Speaker 1: then they'd live a really long time. 1282 01:11:00,520 --> 01:11:04,439 Speaker 2: Well, I mean credible diagnosies. So let's bring this back 1283 01:11:04,479 --> 01:11:10,639 Speaker 2: to economics, okay, because I have to ask what should 1284 01:11:10,680 --> 01:11:15,560 Speaker 2: be the role of economists in issues of public policy, 1285 01:11:16,560 --> 01:11:23,960 Speaker 2: deaths of despair, wealth, health and income inequality? What role 1286 01:11:24,000 --> 01:11:28,120 Speaker 2: should your profession play in trying to make this a 1287 01:11:28,120 --> 01:11:29,080 Speaker 2: little less terrible. 1288 01:11:29,880 --> 01:11:32,599 Speaker 1: Well, let me take back to one of the very 1289 01:11:32,640 --> 01:11:36,000 Speaker 1: first questions you asked me, which is I think about 1290 01:11:36,040 --> 01:11:40,040 Speaker 1: human well being, right, and it's much broader than just money. 1291 01:11:41,040 --> 01:11:44,799 Speaker 1: And economists have been focused on money or the amount 1292 01:11:44,800 --> 01:11:48,120 Speaker 1: of money that people spend, you know, on consumption, on income, 1293 01:11:48,680 --> 01:11:52,559 Speaker 1: and some economists of March Sen would be the leading 1294 01:11:52,600 --> 01:11:55,240 Speaker 1: figure here, has always said you've got to look at 1295 01:11:55,240 --> 01:11:57,880 Speaker 1: mortality rates, you've got to look at health. But there's 1296 01:11:57,920 --> 01:12:01,120 Speaker 1: happiness measures, so lots of other things there too. But 1297 01:12:01,360 --> 01:12:02,840 Speaker 1: you know, this is what I was saying a few 1298 01:12:02,840 --> 01:12:07,200 Speaker 1: minutes ago, that the American economy, just in terms of money, 1299 01:12:07,600 --> 01:12:10,920 Speaker 1: doing so much better than the European countries. But we're 1300 01:12:11,000 --> 01:12:13,800 Speaker 1: dying in drops, the bodies are piling up in the street. 1301 01:12:14,080 --> 01:12:16,760 Speaker 1: In what sense can you say we're doing well? And 1302 01:12:16,840 --> 01:12:19,559 Speaker 1: I think economists just have to get much broader about 1303 01:12:19,680 --> 01:12:21,320 Speaker 1: what they think about. Doing well. 1304 01:12:21,400 --> 01:12:24,800 Speaker 2: Means is that the phrase economism is that where that 1305 01:12:24,840 --> 01:12:27,160 Speaker 2: comes from ignoring not really. 1306 01:12:27,200 --> 01:12:30,040 Speaker 1: I mean economism is more like the minimum wage stuff 1307 01:12:30,080 --> 01:12:33,360 Speaker 1: you use a simple textbook, And that was James Quack 1308 01:12:33,960 --> 01:12:36,280 Speaker 1: calling that term, but it's no. I think it's just 1309 01:12:36,320 --> 01:12:39,320 Speaker 1: when you economists do policy and they think about people 1310 01:12:39,320 --> 01:12:43,000 Speaker 1: getting better off or worse off, they're thinking about unemployment 1311 01:12:43,080 --> 01:12:46,400 Speaker 1: and jobs and money, and they're not really thinking about 1312 01:12:46,920 --> 01:12:50,479 Speaker 1: whether people are flourishing or not. 1313 01:12:50,840 --> 01:12:53,479 Speaker 2: Let's take that another step. When I think of how 1314 01:12:54,080 --> 01:12:57,640 Speaker 2: economists play into the role of things like this, the 1315 01:12:57,680 --> 01:13:03,360 Speaker 2: focus seems to be things like efficiency, productivity, not life 1316 01:13:03,360 --> 01:13:09,040 Speaker 2: satisfaction or happiness. How do you steer the profession towards 1317 01:13:09,120 --> 01:13:12,280 Speaker 2: being a little more holistic and looking at the whole picture, 1318 01:13:12,439 --> 01:13:14,040 Speaker 2: not just the dollars and cents. 1319 01:13:14,200 --> 01:13:16,799 Speaker 1: Well, what made me steer back was these deaths of despair, 1320 01:13:16,880 --> 01:13:20,479 Speaker 1: because you can't talk about them in ordinary economics language. 1321 01:13:20,520 --> 01:13:24,000 Speaker 1: There's something else going on, and I think the sociologists, 1322 01:13:24,000 --> 01:13:27,400 Speaker 1: many of the good sociologists, have really much better handle 1323 01:13:27,880 --> 01:13:32,000 Speaker 1: on what how people's lives are coming apart with de industrialization, 1324 01:13:32,160 --> 01:13:33,360 Speaker 1: for instance, So well. 1325 01:13:33,840 --> 01:13:36,439 Speaker 2: Let me interrupt you a second. In the other book 1326 01:13:36,439 --> 01:13:38,959 Speaker 2: which I didn't read but kind of skimmed an online 1327 01:13:38,960 --> 01:13:43,639 Speaker 2: outlearn you do turn that into an economic analysis. It's 1328 01:13:43,720 --> 01:13:47,040 Speaker 2: not just woe is us. These are the deaths of despair. 1329 01:13:47,560 --> 01:13:53,080 Speaker 2: You correlate it to regional income and health education levels. 1330 01:13:53,560 --> 01:13:56,720 Speaker 2: You really bring in a lot of things I think 1331 01:13:56,760 --> 01:14:01,400 Speaker 2: of as classical economics into analyzing deaths of despairs. Is 1332 01:14:01,439 --> 01:14:01,920 Speaker 2: that fair? 1333 01:14:02,160 --> 01:14:05,160 Speaker 1: Yes, But not only we talk about levels of religion, 1334 01:14:05,280 --> 01:14:08,040 Speaker 1: how people have checked out of going to churches anymore. 1335 01:14:08,920 --> 01:14:10,679 Speaker 2: We talk about that's community as well. 1336 01:14:10,680 --> 01:14:14,000 Speaker 1: It's not unity. But that's a big difference. Economists don't 1337 01:14:14,000 --> 01:14:17,400 Speaker 1: talk about community at all, whereas sociologists spend a lot 1338 01:14:17,400 --> 01:14:21,160 Speaker 1: of time thinking about community. And so their chain would 1339 01:14:21,200 --> 01:14:24,360 Speaker 1: be here's the wages in some place in the rust 1340 01:14:24,360 --> 01:14:27,360 Speaker 1: belt or something. The wages go down, the jobs go away. 1341 01:14:27,640 --> 01:14:30,160 Speaker 1: But it's not just the jobs. I mean, it's the schools, 1342 01:14:30,200 --> 01:14:34,400 Speaker 1: it's the police force, it's the you know, community. Bob 1343 01:14:34,479 --> 01:14:37,519 Speaker 1: Putnam wrote this fabulous book on bowling alone, you know 1344 01:14:37,640 --> 01:14:41,760 Speaker 1: and social capital. His bowling alone guy was bowling in 1345 01:14:41,800 --> 01:14:44,919 Speaker 1: a union hall, or no unions in the private sector anymore. 1346 01:14:44,960 --> 01:14:47,599 Speaker 1: You know, and that was an important sort of power 1347 01:14:47,640 --> 01:14:51,759 Speaker 1: for ordinary working people. So I think power is incredibly important, 1348 01:14:51,760 --> 01:14:54,000 Speaker 1: and I think economists have just lost it there. 1349 01:14:54,160 --> 01:14:56,479 Speaker 2: So I want to tie this back to economics, and 1350 01:14:56,520 --> 01:14:59,760 Speaker 2: I'm going to share an anecdote, will you. So during 1351 01:14:59,800 --> 01:15:03,120 Speaker 2: the pandemic in the first few months, we're locked down. 1352 01:15:03,280 --> 01:15:06,160 Speaker 2: You can't really do anything. You're a little bored. My 1353 01:15:06,280 --> 01:15:09,400 Speaker 2: wife and I, we live out on Long Island. We 1354 01:15:09,439 --> 01:15:11,719 Speaker 2: would get in the car and go for a ride 1355 01:15:12,240 --> 01:15:16,080 Speaker 2: and just drive around different towns where perhaps we might 1356 01:15:16,120 --> 01:15:19,840 Speaker 2: not have been previously. And to me, everything is an 1357 01:15:19,880 --> 01:15:23,720 Speaker 2: economic study. Whatever I do, I try and find a 1358 01:15:23,760 --> 01:15:27,639 Speaker 2: way to turn it back into economic data. And one 1359 01:15:27,720 --> 01:15:32,080 Speaker 2: of the things I noticed is that towns that had 1360 01:15:33,000 --> 01:15:37,479 Speaker 2: robust public spaces could be a waterfront beach, could be 1361 01:15:37,560 --> 01:15:41,519 Speaker 2: a large park, athletic fields, whatever seemed to be open 1362 01:15:41,640 --> 01:15:47,120 Speaker 2: to the public and was a useful recreational area. Those 1363 01:15:47,160 --> 01:15:53,160 Speaker 2: seemed to be affiliated more with wealthier towns. Now I 1364 01:15:53,200 --> 01:15:57,240 Speaker 2: can't figure out which came first. Did the town become 1365 01:15:57,320 --> 01:16:02,639 Speaker 2: wealthy because they had this attractive area and a lot 1366 01:16:02,680 --> 01:16:05,639 Speaker 2: of people wanted to live by it, or do only 1367 01:16:05,680 --> 01:16:08,800 Speaker 2: wealthy towns are only they able to afford these sorts 1368 01:16:08,840 --> 01:16:11,360 Speaker 2: of things. So it's a little bit of a chicken 1369 01:16:11,479 --> 01:16:15,080 Speaker 2: or an egg. But it comes back to if there's 1370 01:16:15,120 --> 01:16:20,760 Speaker 2: a robust sense of community, what does that mean for inequality, 1371 01:16:20,800 --> 01:16:24,360 Speaker 2: what does it mean for general happiness? And does that 1372 01:16:24,520 --> 01:16:28,719 Speaker 2: reduce those sort of deaths of despair that you've highlighted. 1373 01:16:28,800 --> 01:16:33,240 Speaker 1: I think it probably does, And I think that I'm 1374 01:16:33,280 --> 01:16:35,519 Speaker 1: not sure you have to disentangle the chicken and egg. 1375 01:16:35,560 --> 01:16:37,720 Speaker 1: And I think we're on the same page here that 1376 01:16:37,840 --> 01:16:41,679 Speaker 1: you know, I'm an economist, you know you're in cognist. 1377 01:16:41,920 --> 01:16:45,680 Speaker 2: I'm not really, but I'm fascinated by the wage and 1378 01:16:45,760 --> 01:16:46,640 Speaker 2: the wealth. 1379 01:16:46,280 --> 01:16:49,240 Speaker 1: That's coming into the community is the driving of this thing, right. 1380 01:16:49,320 --> 01:16:51,920 Speaker 1: But you know, if people lose their jobs, for instance, 1381 01:16:51,920 --> 01:16:54,320 Speaker 1: you can't just give them the money to make it up, 1382 01:16:54,360 --> 01:16:59,479 Speaker 1: and any we don't, okay. And those things that happen 1383 01:16:59,520 --> 01:17:02,880 Speaker 1: in the community, like the destruction of those open spaces, 1384 01:17:02,920 --> 01:17:06,280 Speaker 1: the destruction of the public library, the destruction of the schools, 1385 01:17:06,800 --> 01:17:09,519 Speaker 1: you know, the loss of unions and things. Those are 1386 01:17:09,640 --> 01:17:12,519 Speaker 1: aspects of people life that are not summarized by the 1387 01:17:12,560 --> 01:17:17,040 Speaker 1: amount of money they spend. So those public goods, those 1388 01:17:17,080 --> 01:17:21,040 Speaker 1: public spaces are important to people, but They're not just 1389 01:17:21,120 --> 01:17:23,439 Speaker 1: the money they get, right, it was just the money 1390 01:17:23,479 --> 01:17:25,519 Speaker 1: that mattered to them. They would never invest in those 1391 01:17:25,520 --> 01:17:26,640 Speaker 1: public spices. 1392 01:17:26,920 --> 01:17:30,160 Speaker 2: So I'm glad you brought that up because part of 1393 01:17:30,160 --> 01:17:33,880 Speaker 2: the reason you won the Nobel Prize was saying, why 1394 01:17:33,920 --> 01:17:37,000 Speaker 2: are we looking at people's income? We should really look 1395 01:17:37,040 --> 01:17:40,120 Speaker 2: at how consumers spend their money, and that gives us 1396 01:17:40,120 --> 01:17:44,600 Speaker 2: a better way to evaluate, especially the bottom quartile or 1397 01:17:44,640 --> 01:17:51,360 Speaker 2: so tell us about this kind of error by economics 1398 01:17:51,400 --> 01:17:54,320 Speaker 2: focusing on income instead of focusing on consumption. 1399 01:17:54,880 --> 01:17:58,720 Speaker 1: Well, in the current speak that I'm talking about now, 1400 01:17:58,800 --> 01:18:00,840 Speaker 1: I think of income and consumption is sort of the 1401 01:18:00,880 --> 01:18:03,120 Speaker 1: same time. Huh right, I just want to get away 1402 01:18:03,120 --> 01:18:06,000 Speaker 1: from money. I want to say that their marriages are 1403 01:18:06,000 --> 01:18:09,639 Speaker 1: really important to them. Sure, and marriages are dysenterating among 1404 01:18:09,680 --> 01:18:11,479 Speaker 1: people without a behavior exactly? 1405 01:18:11,479 --> 01:18:11,920 Speaker 2: Oh is it? 1406 01:18:11,960 --> 01:18:12,080 Speaker 1: So? 1407 01:18:12,560 --> 01:18:15,200 Speaker 2: US has been about a fifty percent divorce rate for 1408 01:18:15,600 --> 01:18:18,760 Speaker 2: since World War Two? What is it for people who 1409 01:18:18,800 --> 01:18:19,479 Speaker 2: don't have. 1410 01:18:19,760 --> 01:18:21,960 Speaker 1: I don't know the rates, but there are graphs and 1411 01:18:22,000 --> 01:18:26,000 Speaker 1: animized book. And what happened was divorce went up for everybody, 1412 01:18:26,560 --> 01:18:28,960 Speaker 1: and then it stopped going up for people with a 1413 01:18:29,000 --> 01:18:31,920 Speaker 1: college degree, and it's still going up for people without 1414 01:18:31,960 --> 01:18:36,240 Speaker 1: a degree. So you get these serial cohabitations, you know, 1415 01:18:36,400 --> 01:18:39,439 Speaker 1: in which men and women get together, they don't get married. 1416 01:18:39,960 --> 01:18:42,760 Speaker 1: The woman doesn't think the guy has got enough prospects, 1417 01:18:43,200 --> 01:18:45,960 Speaker 1: she doesn't stop her having a couple of kids with him, right, 1418 01:18:46,080 --> 01:18:48,439 Speaker 1: and then she trades him in for a better model, 1419 01:18:48,479 --> 01:18:51,719 Speaker 1: as they were. And so you get these families which 1420 01:18:51,800 --> 01:18:56,240 Speaker 1: the sociologists have studied in great depth of people. You know, 1421 01:18:56,360 --> 01:18:59,000 Speaker 1: men in their fifties who have maybe six kids, but 1422 01:18:59,040 --> 01:19:00,880 Speaker 1: they don't know any of them because they're all living 1423 01:19:00,920 --> 01:19:03,519 Speaker 1: with other men. Well, that du to your life, and 1424 01:19:03,560 --> 01:19:06,240 Speaker 1: that's not just sort of a consumption thing. That's your 1425 01:19:06,320 --> 01:19:09,040 Speaker 1: life coming apart. You know, the things that give you 1426 01:19:09,160 --> 01:19:11,519 Speaker 1: meaning are just not there anymore. 1427 01:19:11,840 --> 01:19:17,600 Speaker 2: The household formation failing to gel is very significant, yeah, 1428 01:19:17,360 --> 01:19:20,160 Speaker 2: and more significant for people without color absolutely. 1429 01:19:20,240 --> 01:19:22,360 Speaker 1: And the same is true for pain, for instance. Not 1430 01:19:22,479 --> 01:19:24,519 Speaker 1: pain is hard to measure, but if you look at 1431 01:19:24,560 --> 01:19:29,160 Speaker 1: something that people usually wouldn't lie about, like psiatic pain, 1432 01:19:29,240 --> 01:19:32,240 Speaker 1: you know specific enough if you had it, you would 1433 01:19:32,240 --> 01:19:34,240 Speaker 1: know about it, and you wouldn't say you had it. 1434 01:19:34,479 --> 01:19:37,240 Speaker 1: That's gone up through the roof. For people without a BEA. 1435 01:19:37,720 --> 01:19:40,240 Speaker 2: The assumption is they're more likely to be in a 1436 01:19:40,320 --> 01:19:43,960 Speaker 2: trade or some doesn't do it from manual labor that 1437 01:19:44,040 --> 01:19:46,080 Speaker 2: leads to that or no. 1438 01:19:46,360 --> 01:19:48,400 Speaker 1: In fact that people have looked at that and it 1439 01:19:48,439 --> 01:19:51,600 Speaker 1: doesn't work because actually the jobs they're doing in McDonald's 1440 01:19:51,600 --> 01:19:54,519 Speaker 1: are an Amazon warehouse. They may not be ideal, but 1441 01:19:54,560 --> 01:19:57,040 Speaker 1: they're not as dangerous working in a car assembly plant 1442 01:19:57,200 --> 01:19:58,000 Speaker 1: wherever they were working. 1443 01:19:58,080 --> 01:19:59,439 Speaker 2: Where they may have a college degree. 1444 01:19:59,680 --> 01:20:02,719 Speaker 1: Well they have, but the point is that you can't 1445 01:20:02,800 --> 01:20:05,879 Speaker 1: explain the rising pain by the changing job makes. 1446 01:20:05,880 --> 01:20:09,280 Speaker 2: So it's not just physical labor. The degree is very 1447 01:20:09,400 --> 01:20:10,840 Speaker 2: very significant, seems to. 1448 01:20:10,760 --> 01:20:13,040 Speaker 1: Be, and we don't really know what produces that. It's 1449 01:20:13,120 --> 01:20:15,880 Speaker 1: like half the pup Well's. I don't want to quote 1450 01:20:15,880 --> 01:20:18,919 Speaker 1: a number, but a large number of Americans suffer from 1451 01:20:19,360 --> 01:20:22,600 Speaker 1: non specific lower back pain for its rights, which the 1452 01:20:22,600 --> 01:20:26,400 Speaker 1: medical system has no idea what to do with. Again, 1453 01:20:26,960 --> 01:20:28,599 Speaker 1: less less than a college degree. 1454 01:20:29,120 --> 01:20:30,640 Speaker 2: Wow, that's unbelievable. 1455 01:20:30,920 --> 01:20:34,360 Speaker 1: So this really is a story of people's lives coming apart. 1456 01:20:35,280 --> 01:20:39,679 Speaker 2: So the question is as a society, as a nation, uh, 1457 01:20:39,760 --> 01:20:43,240 Speaker 2: and not just economists but all of us, what should 1458 01:20:43,280 --> 01:20:48,000 Speaker 2: we be trying to do to improve the overall standard 1459 01:20:48,040 --> 01:20:51,960 Speaker 2: of living throughout the United States? What what else can 1460 01:20:52,000 --> 01:20:55,959 Speaker 2: we be doing? Besides mandating a college degree. 1461 01:20:56,320 --> 01:20:58,680 Speaker 1: I don't think mandating and college degree would nestlely do 1462 01:20:58,720 --> 01:21:01,160 Speaker 1: it because it's the social function of the college degree 1463 01:21:01,280 --> 01:21:04,639 Speaker 1: or the college degrees. So think one of my favorite 1464 01:21:04,680 --> 01:21:06,479 Speaker 1: things that gets me into trouble, that would get me 1465 01:21:06,520 --> 01:21:09,040 Speaker 1: into trouble in this building is I think we ought 1466 01:21:09,040 --> 01:21:12,400 Speaker 1: to be much more friendly to unions and that working 1467 01:21:12,439 --> 01:21:15,639 Speaker 1: people need more power. There's hardly any members of Congress 1468 01:21:15,680 --> 01:21:17,960 Speaker 1: who don't have a college degree. For instance, I think 1469 01:21:18,000 --> 01:21:21,880 Speaker 1: something like two percent of all state legislators do not 1470 01:21:21,960 --> 01:21:23,000 Speaker 1: have a college degree. 1471 01:21:23,080 --> 01:21:23,400 Speaker 2: Wow. 1472 01:21:23,720 --> 01:21:26,519 Speaker 1: And I always think of going back to Britain in 1473 01:21:26,600 --> 01:21:30,599 Speaker 1: nineteen forty five when Clement Attlee was the socialist Prime 1474 01:21:30,600 --> 01:21:33,920 Speaker 1: minister immusiately out of the war. Seven members of his 1475 01:21:34,080 --> 01:21:36,759 Speaker 1: cabinet had their first jobs down a coal mine. 1476 01:21:37,040 --> 01:21:37,400 Speaker 2: Wow. 1477 01:21:37,520 --> 01:21:42,280 Speaker 1: Right, And so that was just a completely different you know, 1478 01:21:42,360 --> 01:21:46,080 Speaker 1: and those people had their hands on the levers of power. 1479 01:21:46,600 --> 01:21:50,759 Speaker 1: Probably the greatest foreign secretary that Britain ever had, Ernest Bevin, 1480 01:21:50,960 --> 01:21:55,200 Speaker 1: who was the driving force behind NATO, was the illegitimate 1481 01:21:55,280 --> 01:21:58,519 Speaker 1: child of a prostitute who came up through the union movement. 1482 01:21:58,760 --> 01:22:06,040 Speaker 2: Wow. So I don't see the unions reversing their negative fortunes. 1483 01:22:06,080 --> 01:22:09,600 Speaker 2: This has been a trend. I think you can go 1484 01:22:09,720 --> 01:22:14,720 Speaker 2: back to nineteen eighty with the rescue of Chrysler. It's 1485 01:22:14,760 --> 01:22:18,240 Speaker 2: been pretty much pat Co. Yeah, it's been pretty straight 1486 01:22:18,360 --> 01:22:23,759 Speaker 2: down since that era. So besides the rise of unions, 1487 01:22:23,800 --> 01:22:28,200 Speaker 2: what else could impact this challenge we face. 1488 01:22:28,560 --> 01:22:32,080 Speaker 1: Well, I think that the de industrialization is much more 1489 01:22:32,120 --> 01:22:35,840 Speaker 1: serious than economists have tended to be. And they said, 1490 01:22:35,880 --> 01:22:39,320 Speaker 1: you know, loring tariffs is a good thing. You know, 1491 01:22:40,400 --> 01:22:43,160 Speaker 1: we can almost compensate the losers the gainers get more. 1492 01:22:43,280 --> 01:22:45,800 Speaker 1: But that's all done in terms of money, right, and 1493 01:22:45,840 --> 01:22:49,479 Speaker 1: there's no accounting for the community destruction and all the 1494 01:22:49,560 --> 01:22:50,000 Speaker 1: rest of that. 1495 01:22:50,280 --> 01:22:53,280 Speaker 2: So you raise a really fascinating point. People have been 1496 01:22:53,360 --> 01:22:59,760 Speaker 2: talking lately about reshoring as opposed to offshoring and deglobalization. 1497 01:23:00,120 --> 01:23:06,160 Speaker 2: We've just passed a lot of legislation and funded building 1498 01:23:06,200 --> 01:23:14,360 Speaker 2: semiconductor plants, building wobile plants, anything that's decarbonized. Manufacturing has 1499 01:23:14,360 --> 01:23:17,360 Speaker 2: gotten the green light in the United States. Might this 1500 01:23:17,479 --> 01:23:20,080 Speaker 2: have a positive impact on inequality? 1501 01:23:20,240 --> 01:23:24,040 Speaker 1: Absolutely? I think so. I'm quite enthusiastic about it. And 1502 01:23:24,080 --> 01:23:26,840 Speaker 1: it's not an accident. You know, Janet Yellen is a 1503 01:23:26,840 --> 01:23:30,320 Speaker 1: good friend and she has promoted our Deaths of Despair 1504 01:23:30,400 --> 01:23:33,479 Speaker 1: book every time she gets a chance, for example, And 1505 01:23:33,760 --> 01:23:36,320 Speaker 1: we have other friends in the administration who are very 1506 01:23:36,360 --> 01:23:38,200 Speaker 1: much on the same page on this too. 1507 01:23:38,680 --> 01:23:39,920 Speaker 2: How long does it take? 1508 01:23:40,360 --> 01:23:41,920 Speaker 1: That's a question, isn't it right? 1509 01:23:42,160 --> 01:23:44,479 Speaker 2: So if we're in the midst of you know, all 1510 01:23:44,520 --> 01:23:48,240 Speaker 2: this legislation, the Chips Act, the Inflation Reduction Act, the 1511 01:23:48,240 --> 01:23:53,559 Speaker 2: Infrastructure Bill, these are all ten year funded policies. Ten 1512 01:23:53,680 --> 01:23:57,240 Speaker 2: years from now, might we see a country where the 1513 01:23:57,360 --> 01:24:02,600 Speaker 2: Deaths of Despair has fallen and some of the healthcare outcomes, 1514 01:24:03,000 --> 01:24:07,679 Speaker 2: wealth and income inequalities. Might they be shrinking ten years 1515 01:24:07,720 --> 01:24:08,080 Speaker 2: from now? 1516 01:24:08,360 --> 01:24:09,599 Speaker 1: That's what I'd like to see. 1517 01:24:10,200 --> 01:24:12,920 Speaker 2: So I know I only have you for a limited 1518 01:24:12,960 --> 01:24:16,240 Speaker 2: amount of time, Why don't I jump to my favorite 1519 01:24:16,360 --> 01:24:20,040 Speaker 2: questions that I ask all our guests? Okay, starting with 1520 01:24:21,000 --> 01:24:23,680 Speaker 2: what what has been keeping you entertain these days? What 1521 01:24:23,800 --> 01:24:25,640 Speaker 2: are you what are you watching or listening to? 1522 01:24:26,479 --> 01:24:31,120 Speaker 1: Well? I was a late comer to podcast, but I've 1523 01:24:31,160 --> 01:24:33,920 Speaker 1: done a fair number like this, and some of the 1524 01:24:33,920 --> 01:24:37,280 Speaker 1: people like I like Cardiff Garcia's podcast The New. 1525 01:24:37,200 --> 01:24:38,680 Speaker 2: Bar Ft is that where he is. 1526 01:24:38,760 --> 01:24:41,200 Speaker 1: He used to be the ft but now he's independent. 1527 01:24:41,280 --> 01:24:44,400 Speaker 1: He has a podcast called The New Bizarre which I 1528 01:24:44,520 --> 01:24:48,120 Speaker 1: like a lot. The New Bizarre Okay, it's not Bizarre, 1529 01:24:48,240 --> 01:24:53,080 Speaker 1: but bizzarre as an Arab market, right, and he has 1530 01:24:53,120 --> 01:24:55,559 Speaker 1: a very entertaining range of guests, and I like him. 1531 01:24:55,920 --> 01:24:58,000 Speaker 1: The other one that's a bit different is The New 1532 01:24:58,080 --> 01:25:06,080 Speaker 1: Yorker has writers and sas choose one of their favorite 1533 01:25:06,080 --> 01:25:12,960 Speaker 1: pieces of fiction and reads it on a podcast someone else's, 1534 01:25:14,240 --> 01:25:18,959 Speaker 1: and then the fiction editor of The New Yorker, Deborah Triesman, 1535 01:25:19,320 --> 01:25:22,639 Speaker 1: who was Danny Conneman's daughter in law, I think huh, 1536 01:25:23,400 --> 01:25:29,040 Speaker 1: discusses the in a lengthy conversation after the reading. And 1537 01:25:29,120 --> 01:25:32,000 Speaker 1: I find those absolutely fascinating. I mean, I've always liked 1538 01:25:32,000 --> 01:25:37,120 Speaker 1: short stories, and hearing people really people who spend their 1539 01:25:37,120 --> 01:25:40,400 Speaker 1: lives thinking about short stories talking about them is quite 1540 01:25:40,439 --> 01:25:43,000 Speaker 1: a revelation. So those are two of my favorite parts. 1541 01:25:43,040 --> 01:25:46,200 Speaker 2: I have a flight coming up. I'm gonna definitely download 1542 01:25:46,240 --> 01:25:46,639 Speaker 2: some of those. 1543 01:25:46,720 --> 01:25:47,840 Speaker 1: Yeah. Absolutely. 1544 01:25:48,520 --> 01:25:52,000 Speaker 2: Let's talk about mentors who helped shape your career. 1545 01:25:54,040 --> 01:25:57,439 Speaker 1: Someone we haven't talked about was a man called Sir 1546 01:25:57,560 --> 01:26:03,120 Speaker 1: Richard Stone, who was a who worked for Canes during 1547 01:26:03,120 --> 01:26:05,599 Speaker 1: the War on helping to pay for the war when 1548 01:26:05,680 --> 01:26:08,240 Speaker 1: Kines was working on that, and he got an l 1549 01:26:08,280 --> 01:26:11,800 Speaker 1: price for his work on national income accounting, and I 1550 01:26:11,800 --> 01:26:14,800 Speaker 1: always wanted to be like him. And he was very 1551 01:26:14,880 --> 01:26:17,759 Speaker 1: kind to me, and you know, he had a wonderful 1552 01:26:17,840 --> 01:26:21,200 Speaker 1: dinner table where all sorts of interesting people came for meals. 1553 01:26:22,320 --> 01:26:26,160 Speaker 1: He was a real wine connoisseur, and he wrote beautifully 1554 01:26:26,520 --> 01:26:28,599 Speaker 1: and he was a real imparasis. So these were all 1555 01:26:28,600 --> 01:26:29,800 Speaker 1: the things I wanted to be. 1556 01:26:30,479 --> 01:26:32,160 Speaker 2: How did you know him. 1557 01:26:32,320 --> 01:26:34,200 Speaker 1: Well, I was just when I came back from the 1558 01:26:34,240 --> 01:26:39,559 Speaker 1: Bank of England, which I was so memorably unsuccessful. He 1559 01:26:39,680 --> 01:26:43,240 Speaker 1: had a research project funded by someone or other and 1560 01:26:43,280 --> 01:26:46,960 Speaker 1: I was a lowly research assistant on that for five 1561 01:26:47,040 --> 01:26:50,240 Speaker 1: years or something, so about the lowest job you can 1562 01:26:50,280 --> 01:26:52,479 Speaker 1: ever have in academia, I think. 1563 01:26:52,720 --> 01:26:55,120 Speaker 2: So let's talk about books. What are some of your 1564 01:26:55,200 --> 01:26:57,320 Speaker 2: favorites and what are you reading right now? 1565 01:26:58,160 --> 01:27:01,600 Speaker 1: Well? I like detective novels, though I think of that 1566 01:27:01,680 --> 01:27:04,520 Speaker 1: as a sort of guilty pleasure, and being a good Calvinist, 1567 01:27:04,600 --> 01:27:06,720 Speaker 1: I tried to ration that a little bit. 1568 01:27:06,800 --> 01:27:07,280 Speaker 2: Uh huh. 1569 01:27:07,320 --> 01:27:12,799 Speaker 1: I love the uh the Ian Rankin books about Edinburgh, 1570 01:27:13,040 --> 01:27:14,040 Speaker 1: for instance. 1571 01:27:13,640 --> 01:27:17,040 Speaker 2: And Rankin Ian Rankin Ian Rankin gotcha. 1572 01:27:17,360 --> 01:27:20,920 Speaker 1: And he has a detective called John Reebis who's one 1573 01:27:20,960 --> 01:27:26,840 Speaker 1: of these emotionally underdeveloped cops who is very smart but 1574 01:27:27,400 --> 01:27:31,360 Speaker 1: has problems with these emotions. I like those a lot, 1575 01:27:33,240 --> 01:27:35,759 Speaker 1: but I read a wider I tried to alternate between 1576 01:27:36,479 --> 01:27:42,200 Speaker 1: work and you know, so I've been reading and Admati's 1577 01:27:42,240 --> 01:27:45,800 Speaker 1: book on the Bankers have No Clothes, but banks alto 1578 01:27:45,840 --> 01:27:48,559 Speaker 1: have been made to have more capital than they have, 1579 01:27:49,720 --> 01:27:52,840 Speaker 1: which I was reading the newspaper yesterday. They're not taking 1580 01:27:53,120 --> 01:27:56,080 Speaker 1: huge ads at National Air, Union station and so on, 1581 01:27:56,680 --> 01:27:58,840 Speaker 1: demanding that they don't have to do that. 1582 01:28:00,160 --> 01:28:02,599 Speaker 2: It's going to affect profitability if they do well, that's. 1583 01:28:02,479 --> 01:28:06,679 Speaker 1: Right, But they're getting profits at the at the expense 1584 01:28:06,760 --> 01:28:08,800 Speaker 1: of putting all the rest of us at risk. Right, 1585 01:28:09,479 --> 01:28:12,200 Speaker 1: And you know that that's one of the takers that 1586 01:28:12,240 --> 01:28:14,840 Speaker 1: we're talking about as opposed to makers that we need 1587 01:28:14,920 --> 01:28:17,400 Speaker 1: to do something about. And we haven't really talked about 1588 01:28:17,400 --> 01:28:19,280 Speaker 1: banks that I don't know as much about them as 1589 01:28:19,320 --> 01:28:21,920 Speaker 1: I know about healthcare. But there's a similar amount of 1590 01:28:22,000 --> 01:28:23,479 Speaker 1: rent seeking going on in. 1591 01:28:23,400 --> 01:28:25,920 Speaker 2: Both those to say the very least. 1592 01:28:25,880 --> 01:28:28,280 Speaker 1: To say the very least in both of those industries. 1593 01:28:28,800 --> 01:28:32,280 Speaker 1: And I'm reading Paul Thereu's in your book about George 1594 01:28:32,400 --> 01:28:37,639 Speaker 1: orwoll uh And it's a novel and it's a novel 1595 01:28:37,680 --> 01:28:40,799 Speaker 1: about Oral's early days in the Burmese police. 1596 01:28:41,560 --> 01:28:43,080 Speaker 2: Huh, that sounds really interesting. 1597 01:28:43,120 --> 01:28:44,000 Speaker 1: It is very good. 1598 01:28:44,160 --> 01:28:47,720 Speaker 2: Our final two questions, what sort of advice would you 1599 01:28:47,760 --> 01:28:52,000 Speaker 2: give a recent college grad interested in a career in 1600 01:28:52,080 --> 01:28:54,479 Speaker 2: any of the sort of economics work that you've done. 1601 01:28:55,479 --> 01:28:58,760 Speaker 1: I think it's it's advice that I would probably have 1602 01:28:58,840 --> 01:29:03,680 Speaker 1: moved away from. But it's still true, which is, you 1603 01:29:03,760 --> 01:29:06,120 Speaker 1: really need to learn as much method as you can handle, 1604 01:29:06,800 --> 01:29:11,559 Speaker 1: and in finance and in many other things too. I mean, 1605 01:29:11,720 --> 01:29:14,000 Speaker 1: I don't really subscribe to the view that you can't 1606 01:29:14,000 --> 01:29:18,400 Speaker 1: think straight unless you can do it mathematically. But you know, 1607 01:29:18,560 --> 01:29:21,160 Speaker 1: I remember my son saying to me when he was fourteen, 1608 01:29:21,680 --> 01:29:23,800 Speaker 1: He said, would you have regarded yourself as a well 1609 01:29:23,880 --> 01:29:30,240 Speaker 1: qualified mathematician in your time? But not like you? So 1610 01:29:31,040 --> 01:29:33,760 Speaker 1: I think that's a lot of these people have done very, 1611 01:29:33,840 --> 01:29:38,880 Speaker 1: very well. So that's a piece of advice I would 1612 01:29:39,040 --> 01:29:41,559 Speaker 1: it's a bit late by the time you graduated from college. 1613 01:29:42,320 --> 01:29:45,080 Speaker 1: If you cadure in the social department, that's probably not 1614 01:29:45,280 --> 01:29:46,080 Speaker 1: the best advice. 1615 01:29:46,840 --> 01:29:49,000 Speaker 2: And our final question, what do you know about the 1616 01:29:49,000 --> 01:29:53,120 Speaker 2: world of economics today? You wish you knew forty or 1617 01:29:53,120 --> 01:29:56,920 Speaker 2: so years ago when you were leaving the Bank of England. 1618 01:29:59,360 --> 01:30:02,920 Speaker 1: Not much actually, I think for me it's been a 1619 01:30:02,960 --> 01:30:06,559 Speaker 1: great adventure all along. And I love learning new stuff, 1620 01:30:07,200 --> 01:30:10,479 Speaker 1: and I love reading stuff and their real ideas there 1621 01:30:10,520 --> 01:30:14,040 Speaker 1: that I didn't know before. And I've been incredibly important 1622 01:30:14,040 --> 01:30:16,519 Speaker 1: to fortunate. I was going to almost said, unfortunately, I've 1623 01:30:16,520 --> 01:30:19,680 Speaker 1: been incredibly fortunate Mary. And you know I got the 1624 01:30:19,760 --> 01:30:23,160 Speaker 1: Nobel Prize in twenty fifteen. The work that and Case 1625 01:30:23,200 --> 01:30:25,200 Speaker 1: and I have done, which is what both of us 1626 01:30:25,240 --> 01:30:28,599 Speaker 1: are best known for, was done after that. Really, so 1627 01:30:28,760 --> 01:30:31,400 Speaker 1: it's like a whole new career for me. 1628 01:30:31,840 --> 01:30:35,080 Speaker 2: With the Nobel Prize focusing attention on that work. 1629 01:30:35,280 --> 01:30:38,160 Speaker 1: It certainly did because the first paper in the precedings 1630 01:30:38,200 --> 01:30:41,719 Speaker 1: in National Academy of Sciences came out three days after 1631 01:30:41,800 --> 01:30:46,000 Speaker 1: the Nobel Prize by coincidence. And I can tell you 1632 01:30:46,080 --> 01:30:48,559 Speaker 1: when you get the Nobel Prize, it really is being 1633 01:30:48,640 --> 01:30:51,400 Speaker 1: like hit by a bus. You know, there were reporters 1634 01:30:51,439 --> 01:30:54,840 Speaker 1: on our lawn about half an hour after the announcement. 1635 01:30:54,920 --> 01:30:56,559 Speaker 2: You didn't get the did you get the phone call? 1636 01:30:56,600 --> 01:30:57,719 Speaker 2: Where who is this? Really? 1637 01:30:57,840 --> 01:31:00,640 Speaker 1: Yeah? I knew the person I was took to. I 1638 01:31:00,680 --> 01:31:05,240 Speaker 1: know you did pretty well. Yeah, so and he said angus, 1639 01:31:05,320 --> 01:31:07,960 Speaker 1: this is not a prank, and I said, tourist. And 1640 01:31:08,000 --> 01:31:10,439 Speaker 1: I never thought it was a preak until you said that. 1641 01:31:10,840 --> 01:31:13,120 Speaker 2: And now I'm wondering, So I think it was Dick 1642 01:31:13,200 --> 01:31:15,759 Speaker 2: Taylor said he was in the shower and his wife 1643 01:31:15,760 --> 01:31:18,960 Speaker 2: answered the phone. Tell he's and yells from the shower 1644 01:31:19,080 --> 01:31:22,800 Speaker 2: tell them thanks. But I'm busy thinking it's someone's just 1645 01:31:22,800 --> 01:31:25,519 Speaker 2: pulling his leg, right, right, I could be getting it wrong. 1646 01:31:25,520 --> 01:31:26,120 Speaker 2: It may not be. 1647 01:31:26,680 --> 01:31:28,920 Speaker 1: I hadn't heard that story, but it's like you hear 1648 01:31:28,960 --> 01:31:31,360 Speaker 1: all sorts of things like that, right, yeah, yeah, sure. 1649 01:31:31,720 --> 01:31:33,960 Speaker 1: But then this paper came out about a week later, 1650 01:31:34,439 --> 01:31:37,280 Speaker 1: and it was like being hit by ten buses because 1651 01:31:37,280 --> 01:31:40,600 Speaker 1: it had this enormous impact. Right, And you know that 1652 01:31:40,720 --> 01:31:42,400 Speaker 1: one of the best stories I think I'm tell in 1653 01:31:42,520 --> 01:31:45,160 Speaker 1: the book was in those days, and I think they've 1654 01:31:45,200 --> 01:31:49,320 Speaker 1: resumed it again. The American Nobel's got to go to 1655 01:31:49,360 --> 01:31:53,679 Speaker 1: the Oval Office and meet the president, right. And when 1656 01:31:54,160 --> 01:31:57,080 Speaker 1: we were in, there's a little ante room outside the 1657 01:31:57,120 --> 01:32:01,200 Speaker 1: Oval Office which had these Norman Rocks whole paintings which 1658 01:32:01,320 --> 01:32:04,920 Speaker 1: are not there anymore. They belong to someone else. And 1659 01:32:05,800 --> 01:32:08,920 Speaker 1: a voice, someone came from inside and said, would Deaton 1660 01:32:09,040 --> 01:32:11,559 Speaker 1: and Case go to the front of the line please, 1661 01:32:11,560 --> 01:32:14,679 Speaker 1: which we were not there alphabetically, And the door opened 1662 01:32:14,680 --> 01:32:17,840 Speaker 1: and it was not a flunky. It was Obama. Oh 1663 01:32:17,880 --> 01:32:21,879 Speaker 1: really yeah, And so I said, mister President, I'm delighted 1664 01:32:21,920 --> 01:32:24,120 Speaker 1: to meet you, and I'd like to introduce you. And 1665 01:32:24,160 --> 01:32:27,920 Speaker 1: he said, Professor Case needs no introduction. Oh really, I 1666 01:32:27,960 --> 01:32:30,920 Speaker 1: am familiar with her work and I'm a great fan. Wow. 1667 01:32:31,040 --> 01:32:33,800 Speaker 1: And we spent almost all the time in the Oval 1668 01:32:33,840 --> 01:32:36,240 Speaker 1: office talking about the paper that had come out three 1669 01:32:36,320 --> 01:32:39,080 Speaker 1: days before. Hu and he knew it inside out. 1670 01:32:39,080 --> 01:32:41,000 Speaker 2: Your wife must have been walking on air. 1671 01:32:41,120 --> 01:32:44,080 Speaker 1: Yeah, she came out of the White House floating. I 1672 01:32:44,120 --> 01:32:44,960 Speaker 1: think I'm in love. 1673 01:32:46,640 --> 01:32:51,439 Speaker 2: Fascinating, Professor, Thank you for being so generous with your time. 1674 01:32:52,240 --> 01:32:56,080 Speaker 2: We have been speaking with Sir Angus Deaton, winner of 1675 01:32:56,120 --> 01:33:01,040 Speaker 2: the twenty fifteen Nobel Prize in Economic Sciences. His latest book, 1676 01:33:01,240 --> 01:33:06,680 Speaker 2: Economics in America, An Immigrant Economist, explores the Land of Inequality, 1677 01:33:07,320 --> 01:33:11,920 Speaker 2: is out today. If you enjoy this conversation, well, be 1678 01:33:12,000 --> 01:33:15,160 Speaker 2: sure and check out any of the previous five hundred 1679 01:33:15,160 --> 01:33:19,120 Speaker 2: discussions we've had over the past nine and a half years. 1680 01:33:19,680 --> 01:33:24,400 Speaker 2: You can find those at iTunes, Spotify, YouTube, wherever you 1681 01:33:24,520 --> 01:33:28,960 Speaker 2: find your favorite podcasts. And check out my new podcast, 1682 01:33:29,320 --> 01:33:32,479 Speaker 2: At the Money. It's in the Masters and Business feed 1683 01:33:33,000 --> 01:33:37,720 Speaker 2: and it's short, ten minute conversations about money with some 1684 01:33:37,840 --> 01:33:41,880 Speaker 2: of our favorite Masters and business guests are earning it, 1685 01:33:41,960 --> 01:33:46,040 Speaker 2: spending it, and most importantly, investing it. At the Money 1686 01:33:46,160 --> 01:33:50,080 Speaker 2: wherever you find your favorite podcasts. I would be remiss 1687 01:33:50,200 --> 01:33:52,120 Speaker 2: if I did not thank the Crack team that helps 1688 01:33:52,160 --> 01:33:56,719 Speaker 2: us put these conversations together. My audio engineer is Meredith Frank. 1689 01:33:56,920 --> 01:34:01,080 Speaker 2: Attika Vaalbrun is our project manager, and Wanna Luke is 1690 01:34:01,120 --> 01:34:05,200 Speaker 2: my producer. Sean Russeau is my head of research. Sage 1691 01:34:05,240 --> 01:34:08,640 Speaker 2: Bauman is the head of Podcasts here at Bloomberg, And 1692 01:34:08,840 --> 01:34:12,919 Speaker 2: I'm Barry Griholtz. You've been listening to Masters in Business 1693 01:34:13,560 --> 01:34:14,799 Speaker 2: on Bloomberg Radio.