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Speaker 1: Hi, and welcome back to Bloomberg. Benchmark, a podcast about

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Speaker 1: the global economy, is Thursday, October fifteen. I'm Tori Stowell,

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Speaker 1: a US economics reporter in DC with Bloomberg News, and

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Speaker 1: I'm joined by my co host, Dan Moss, our executive

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Speaker 1: editor for International Economics News, and Akido, our editor for Benchmark,

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Speaker 1: is actually working out of Tokyo this week, so she

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Speaker 1: won't be joining us, but she is here in spirit.

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Speaker 1: She is, and there's good reason for you to be

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Speaker 1: excited today. That's right. I'm so pumped, so excited, probably

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Speaker 1: the most excited I've ever been for anything in my life. Yeah,

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Speaker 1: old twenty two years. That's because we've got Angus Dton

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Speaker 1: with us on the show today. Hopefully that name will

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Speaker 1: ring a bell. It should, because he is a professor

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Speaker 1: at Princeton University and was this week named as the

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Speaker 1: recipient of the two thousand fifteen Nobel Prize in Economics.

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Speaker 1: And it's safe to say in the seven episode life

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Speaker 1: of this show, we've never had someone of that statue

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Speaker 1: in at such an important point in their life. That's right,

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Speaker 1: this is going to be huge. We're very excited. So

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Speaker 1: before he joins us, let's quickly run through his bio.

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Speaker 1: He was born in Edinburgh, Scotland, and received his bachelor's, masters,

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Speaker 1: and PhD degrees, all at Cambridge and all in economics.

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Speaker 1: And he's been teaching at Princeton now for more than

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Speaker 1: thirty years. All at Cambridge. Yes, no Oxford, No Oxford,

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Speaker 1: so it's just the Bridge. His recent research has looked

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Speaker 1: into things like consumer saving, measurements of economic well being,

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Speaker 1: what a concept, poverty, health, and development economics. The official

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Speaker 1: description from the selection committee that gave him the award

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Speaker 1: is quote for his analysis of consumption, poverty and welfare.

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Speaker 1: I was lucky enough to chat with him earlier today

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Speaker 1: in our newsroom, so you may hear a little bit

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Speaker 1: of background noise, but what you'll here's our station and

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Speaker 1: I hope you guys enjoyed as much as I did.

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Speaker 1: For our listeners who don't know, Nobel Prize winners get

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Speaker 1: a call from Sweden and for US laureates that usually

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Speaker 1: turns out to be very early in the morning. So

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Speaker 1: did you have any trouble sleeping the night before? You know,

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Speaker 1: were you expecting boys? Oh no, no, not at all.

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Speaker 1: I mean you know there there there have been several

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Speaker 1: years when it was a possibility, and I've always realized

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Speaker 1: that a possibility is a very different thing from my

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Speaker 1: high probability. Right, So, um, you know, no, it's never

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Speaker 1: cost me any sleep. Good And we get up pretty

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Speaker 1: early in the morning anyway. So my wife Anne, it's

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Speaker 1: also a colleague here, Princeton's already up and I was

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Speaker 1: pretty I was certainly awake. So what time did you

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Speaker 1: actually get the call? Wow, that's very precisely, and uh,

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Speaker 1: what would your what was your reaction, Oh, the light,

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Speaker 1: A little bit of disbelief, not that I thought it

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Speaker 1: wasn't true, just all, my goodness is really happening, right, um.

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Speaker 1: And it was wonderful to talk to two of the

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Speaker 1: I mean I talked to the Germans, or at least

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Speaker 1: once the introductions row, and then I talked to two

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Speaker 1: good friends who remembers the committee, you know, one who

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Speaker 1: used to be one of my colleagues of Princeton and

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Speaker 1: another one who had known for many, many years. So

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Speaker 1: you didn't think it was a prank at least? No, well,

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Speaker 1: I didn't think it was a prank until my friend

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Speaker 1: torst in person said this is not a prank. Though

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Speaker 1: I never thought it was a prank. Why is he

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Speaker 1: telling me that thing with my head. He's trying to

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Speaker 1: make me think it might be a prank, right, trying

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Speaker 1: to stake you out. It is a very funny, very

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Speaker 1: playful guy. Well, your work has proven that you really

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Speaker 1: have to look at the teeny tiny details to understand

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Speaker 1: these big macro econom trends across the world that we

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Speaker 1: talked about on our show. And you said during your

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Speaker 1: press conference at Princeton that measurement is at the center

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Speaker 1: of what you do. So using that as a lens,

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Speaker 1: can you walk us through your work that won you

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Speaker 1: the Nobel Oh? Yes, But one of the things the

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Speaker 1: Nobel Committee was very generous was was citing a broad

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Speaker 1: swaite of work. So it's rather difficult to um take

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Speaker 1: any piece of it and say, you know, this is

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Speaker 1: how I started doing that, this is what led me

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Speaker 1: in this direction. But I remember, you know, very very

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Speaker 1: very early on, I think even before I had a PhD,

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Speaker 1: or before I even thought of getting a PhD. Um

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Speaker 1: And in the days when there were no computers, when

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Speaker 1: you would sit in the library and copyright numbers from

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Speaker 1: statistical abstracts or from reports, and I remember even then thinking, oh,

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Speaker 1: this is really interesting. Now. Of course there's someone poor

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Speaker 1: work in the world. But I would look at these

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Speaker 1: numbers and you know, with a pencil on one hand

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Speaker 1: and e racer in the other hand, and say, well,

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Speaker 1: you know, what are these talents and the fit with

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Speaker 1: the way we think about these things? And then you

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Speaker 1: sort of realize that maybe they sort of didn't or

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Speaker 1: maybe they sort of did. So I remember that activity

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Speaker 1: of just copying down these numbers and hearing the data

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Speaker 1: UM being just very instructive for me and quite enjoyable

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Speaker 1: in a way that I wouldn't have a therapeutic it's

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Speaker 1: sort of therapeutic, but it was also it turned out

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Speaker 1: to be quite scientific UM And for me. You know,

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Speaker 1: one of the greatest things in recent years has been

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Speaker 1: the availability of fast graphics UM, so that you can

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Speaker 1: grow pictures of data and sort of look at them.

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Speaker 1: So here, all of a sudden, there's this tool which

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Speaker 1: enables you to see these numbers and see patterns in

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Speaker 1: these numbers. And you know, I used to feel really

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Speaker 1: bad and that people would say to me, so, what's

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Speaker 1: your hypothesis? You know, why don't you have hypothes says

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Speaker 1: you should be testing hypother says and I would say,

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Speaker 1: I just like playing with the numbers, and I play

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Speaker 1: with the numbers and try to see patterns in them,

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Speaker 1: and then that would relate to other hypotheses that I

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Speaker 1: knew about or other theories that I knew about it,

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Speaker 1: because I don't think it where you start matters. It's

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Speaker 1: always just this business of you know, looking at the numbers,

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Speaker 1: comparing them with what you know and what people think

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Speaker 1: two things together, interpret one in terms of the other,

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Speaker 1: both direct. So you've looked into things looking at these

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Speaker 1: these small numbers, UM, trying to figure out they've been

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Speaker 1: measured right, and you've applied to things like consumer spending

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Speaker 1: and savings, UM, well being and poverty UM. I mean,

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Speaker 1: how did you get interested in that vein of work?

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Speaker 1: And I guess what have you found would have been

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Speaker 1: some of the big conclusions that you've been able to

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Speaker 1: make from your work? Again, I'm you know, one of

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Speaker 1: the things you do if you measure things is you're

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Speaker 1: really standing on the shoulders of others. I mean, it's

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Speaker 1: not like you come up with a indict theory that

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Speaker 1: no one's ever thought about before. Many other people have

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Speaker 1: done that, but that's really not what I do. And

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Speaker 1: I think in several cases, just being really meticulous about

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Speaker 1: thing and really you know, pulling things apart and trying

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Speaker 1: to figure out how they hold together. I did come

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Speaker 1: up with things that people really didn't know about before.

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Speaker 1: And you know, we did a lot of work on

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Speaker 1: UM collecting and processing prices in India and figuring out

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Speaker 1: what it costs for people to live in India. And

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Speaker 1: then that gave you insights on ways in which you

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Speaker 1: could measure poverty, because, after all, you know how much

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Speaker 1: people spend money, but you don't really know what they're

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Speaker 1: getting for that unless you know the prices of things.

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Speaker 1: So I've done a lot of work over the years

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Speaker 1: and trying to find ways of combining these prices into

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Speaker 1: cost of living index numbers UM and also collecting the prices.

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Speaker 1: What sort of prices can you use? I know it

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Speaker 1: sounds sort of tedious, but it doesn't to me. So

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Speaker 1: I mean, let's let's zoom in on India a little

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Speaker 1: bit then, how just how do you scrutinize consumption in

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Speaker 1: a place like that. There's six hundred villages literacy, Sorry

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Speaker 1: I thought I said six hundred thousand, That was all right,

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Speaker 1: And according to the two thousand one sence is there

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Speaker 1: about six? Yeah? Um, so that's a lot and and

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Speaker 1: you know it's probably even more than that. Now given

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Speaker 1: how old that data is? Um, I mean, how do

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Speaker 1: you how do you know the data then is correct?

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Speaker 1: How how do you look at prices and consumption and

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Speaker 1: you compare them to official statistics? I mean, what sort

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Speaker 1: of hurdles can there be in finding good measurements and

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Speaker 1: using good measurements and the widespread use of good measurements? Well,

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Speaker 1: you know that problem you're talking about, which is given

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Speaker 1: you know, six hundred thousand or whatever the number is,

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Speaker 1: how do you how do you find out about all

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Speaker 1: of them? Was actually solved in India in the nineties

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Speaker 1: by Indian scientists who really pioneered this. What you do

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Speaker 1: is you take a statistical sample, so you randomly select

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Speaker 1: some villages and you look at them, and they can

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Speaker 1: stand in for the villages as a whole. But then

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Speaker 1: your other questions is is how you know this is right? Well,

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Speaker 1: that's when there's really no substitute for sort of appearing

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Speaker 1: at the numbers and saying does this make any sense?

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Speaker 1: And can I square this with other things I know?

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Speaker 1: And these numbers consistent with these other numbers and does

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Speaker 1: does picture make any sense? And if it doesn't make

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Speaker 1: any sense, maybe the world is different from what we thought,

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Speaker 1: or maybe there's something wrong with the data. And you're

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Speaker 1: always trying to juggle both of these things at the

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Speaker 1: same time. And a little bit about that also is

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Speaker 1: two of my work unhappiness. First, I think most people,

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Speaker 1: like most economists, are very imbvalent about this. I mean,

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Speaker 1: they think happiness is incredibly important, and it's certainly something

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Speaker 1: that gets a lot of public attention when you write

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Speaker 1: about it. Um. I think my working unhappiness is the

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Speaker 1: only thing I've ever done where I've heard people the

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Speaker 1: supermarket talking about it, for instance, and there was an

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Speaker 1: episode of Oranges that you Black where they talked about it.

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Speaker 1: So it certainly is things are very interesting people. But

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Speaker 1: many people are skeptical as to whether if you ask people,

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Speaker 1: you know that you experienced a lot of happiness, yesity,

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Speaker 1: or you know, on a scale of zeroes at ten,

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Speaker 1: how's your life going. They really wonder about whether those

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Speaker 1: numbers can be treated seriously or not. This is the

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Speaker 1: link between income and happiness, the link between income and well,

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Speaker 1: that's one of the things we looked at So that's

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Speaker 1: a very good example. I mean, you've got these happiness

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Speaker 1: numbers and you say, well, what would happen if those

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Speaker 1: weren't linked to income at all? You know, and then

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Speaker 1: you say, well, maybe these happiness numbers don't really mean anything,

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Speaker 1: or maybe it's just true that income doesn't really matter.

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Speaker 1: And you know, we came out with a bit of

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Speaker 1: bove um, which is that, um, this is the work

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Speaker 1: I did with any common which is nice time because

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Speaker 1: to know about laureates that what, so maybe it's even

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Speaker 1: more credible, But that was you know, what we find

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Speaker 1: is that for people's emotional life, like did you feel

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Speaker 1: a lot of happiness yesterday? Or did you feel a

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Speaker 1: lot of strasssdy? You know, if you had less than

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Speaker 1: sebout seventy five dollars, those things were much worse than

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Speaker 1: you had more of that. But if you had more

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Speaker 1: than seventy five, you know, you didn't experience much more

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Speaker 1: happiness that you provided you as seventy five times. So

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Speaker 1: we concluded from that that your emotional life depended on

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Speaker 1: um sort of having a freedom not to worry about money.

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Speaker 1: You know, I grew up pretty poor, not poor compared

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Speaker 1: with you know, people in India or Africa were really poor,

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Speaker 1: but poor enough so that the worry about money really

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Speaker 1: cast a pall over your life a lot of the time.

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Speaker 1: And so yeah, you know, people would say come out

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Speaker 1: for a beer and anything. Oh, that would be lovely,

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Speaker 1: but I really can't afford they come out and have

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Speaker 1: a beer. And I think those things do undermine people's

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Speaker 1: well being. You know. Friendship is a terribly important thing

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Speaker 1: for people's well being. And if you're scraping money and

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Speaker 1: worrying about the last few cents, then I think that

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Speaker 1: gets in the way. But then we find out these

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Speaker 1: other things about how is your life going, you know,

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Speaker 1: rating your life altogether. That seems to keep on going

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Speaker 1: up with no matter how much money here. Well, speaking

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Speaker 1: of money and and income and poverty, things along that vein,

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Speaker 1: the World Bank just said last week that the number

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Speaker 1: of people living in extreme poverty is set to fall

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Speaker 1: to the lowest on record this year. About nine point

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Speaker 1: six of the global population will live on less than

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Speaker 1: one dollar ninety cents a day this year, and that's

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Speaker 1: the first time that rate has dropped below ten percent,

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Speaker 1: and it also compares to about thirty seven that's pretty

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Speaker 1: big progress. Um so looking at global poverty and what

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Speaker 1: many people consider to be one of your most important contributions,

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Speaker 1: which is your work looking into that. How much more

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Speaker 1: progress is there to do on the front of global

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Speaker 1: poverty and how do we get there? Well, you get there?

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Speaker 1: Love me? Was putting that for Amnente, because that's the

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Speaker 1: hard one. Um, these numbers you quoted, I'm not sure

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Speaker 1: that once you take those very seriously, but the decline

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Speaker 1: from thirty seven to ten, you should take that very seriously, indeed,

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Speaker 1: meaning that things have gotten a lot better. So that's

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Speaker 1: that's statement one, and it's got to be true. And

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Speaker 1: it's just the most wonderful thing about the world over

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Speaker 1: the last thirty years. So that's really terrific. And I

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Speaker 1: think it's got to be right because his squares with

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Speaker 1: all sorts of other things. We know, the decline, you know,

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Speaker 1: the actual amount, I'm not sure totally relevant. Um. The

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Speaker 1: other thing, of course, is that even with ten percent,

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Speaker 1: that's seven million people. You know, that's twice the population

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Speaker 1: United States, are more than twice the population in the

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Speaker 1: United States, and those people are living in something pretty

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Speaker 1: close to total institution. And indeed, it would be like

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Speaker 1: trying to live in the United States on about two

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Speaker 1: bucks a day, and if you managine that, that's pretty

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Speaker 1: hard to managine. And I think that's not far from

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Speaker 1: being the right comparison though. You know, in warmer climbs,

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Speaker 1: people don't need to spend as much of fuel or

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Speaker 1: on healthcare or unclosed song as we would have to hear.

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Speaker 1: But just think of meeting you know, food and basic

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Speaker 1: expenses out of two bucks of ay. So those people

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Speaker 1: are really really, really very poor. And also one shouldn't

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Speaker 1: just kind of poverty in terms of material deprivations. A

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Speaker 1: lot of these people, um, you know, don't kind particularly

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Speaker 1: healthy lives and a lot of there are a lot

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Speaker 1: of kids in Africa who are still dying before their

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Speaker 1: fifth birthday from totally preventable diseases. And the children in India,

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Speaker 1: something like half of them are so short and so

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Speaker 1: small as kids that you know, if you took them

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Speaker 1: to a pediatrician here, the doctor would say, my god,

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Speaker 1: you know, we really got to do something about this kid,

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Speaker 1: way way off the charts. And half of all kids

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Speaker 1: in are like that. So there's a lot to be done. Um,

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Speaker 1: now how exactly to do it? Um? And you know,

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Speaker 1: one of the more controversial things I've written about is

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Speaker 1: I don't think direct two very poor countries, it's very productive.

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Speaker 1: But I think a lot of progress in India and China,

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Speaker 1: which is the big success stories, and the rate of

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Speaker 1: growth at least the rate of production of poverty are

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Speaker 1: ones where aid has not been very important. And we're

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Speaker 1: talking about aid from foreign governments from foreign governments. But

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Speaker 1: I mean, I think countries have to look after their people,

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Speaker 1: and a lot of these countries, including India a lot

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Speaker 1: of the time, are not very effective at providing public services,

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Speaker 1: you know, getting all the kids vaccinated, that doing mother

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Speaker 1: and child, you know, prenatal and postnatal care. So it's

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Speaker 1: really about government being able to take care of its

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Speaker 1: people absolutely while a wanting to and be being able to. Yeah,

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Speaker 1: there are two different things. Spacity problem. Yeah, you wrote

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Speaker 1: a book in two thousand thirteen called The Great Escape

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Speaker 1: that looked at inequality on a global level spanning almost

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Speaker 1: three centuries. The same subject got the French treatment just

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Speaker 1: a year later by Thomas Paquetti his book Capital in

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Speaker 1: the twenty first century, and since then the topic of

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Speaker 1: inequality has become almost ubiquitous around the world. Granted, Patty's

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Speaker 1: book was just about twice as big. I prefer the

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Speaker 1: more concise version. UM, I would say that definitely couple

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Speaker 1: of days as everybody. That's where you got the last

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Speaker 1: laugh there. So well, since then, the topic of inequality

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Speaker 1: has become almost ubiquitous. Why is that? Where is inequality

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Speaker 1: the worst? Um? And why is it on the tips

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Speaker 1: of everyone's tongues right now? It's a really good question.

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Speaker 1: I mean, you know, these are like social movements. It's

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Speaker 1: like saying, you know why you know when I was twelve,

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Speaker 1: was everybody looked at the window and everyone was playing

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Speaker 1: with Zula hopes. UM. So there are certain amount of fashions,

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Speaker 1: but it's terribly important. And you know, Epicoty and his

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Speaker 1: co author Manuel Sias, you know, did a huge public

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Speaker 1: service by looking at the data in new ways and

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Speaker 1: just by pure measurement exercise and showing this incredible increase

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Speaker 1: in wealth at the very top of the income distribution.

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Speaker 1: And I think that paper, which was written maybe twenty

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Speaker 1: years ago now quite a while, UM, really did put

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Speaker 1: the cat among the pigeons, because there was really just

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Speaker 1: this feeling that here was something we didn't know about. UM.

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Speaker 1: There was this extraordinary rise in equality and then over

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Speaker 1: time it seemed to be the case that that was

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Speaker 1: happening in many, many, many, not every many countries around

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Speaker 1: the world. So I think this is terrific. I'm very

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Speaker 1: keen that we have this debate about the good parts

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Speaker 1: of inequality in the bad parts of equality. Um. And

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Speaker 1: you know, it's not a one sided thing. So you

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Speaker 1: can't say the world would be a better place if

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Speaker 1: there was no inequality. There may be an optimal amount

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Speaker 1: of inequality, but I don't know what it is, and

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Speaker 1: neither does anyone else. But that's the sort of thing

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Speaker 1: that people might be thinking about. And it may be

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Speaker 1: that when inequality gets very severe, which is the sort

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Speaker 1: of thing I've written about in the Buck and worried

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Speaker 1: about it, is that then you begin to lose things

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Speaker 1: that you really care about it. I mean, Justice Brand

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Speaker 1: is this wonderful quote about how you know, democracy and

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Speaker 1: extreme inequality are not compatible in the long run. And

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Speaker 1: you know, that's something that I think we should really

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Speaker 1: really worry about, and many people do. It's also become

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Speaker 1: I mean, inequality has become a very politicized thing at

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Speaker 1: this point too. I mean, have you had any political

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Speaker 1: people calling you any presidential candidates possibly, so, um, I

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Speaker 1: think good so that Um No, I mean it's become

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Speaker 1: very political because of course, you know, as my work

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Speaker 1: and others would predict it would, because after all, people

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Speaker 1: are trying to use money to affect the political process. Well, um,

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Speaker 1: I guess the biggest question that remains is what's next.

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Speaker 1: You know, you've you've already run one of the most

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Speaker 1: prestigious prize that you can get as an economist or

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Speaker 1: in many other fields. That is what's next. You're just

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Speaker 1: trying to get back to work or to get just

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Speaker 1: trying to get a lot of fun. I'm having a

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Speaker 1: lot of fun. I mean it's fun to um, and

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Speaker 1: it's been fun um actually reading the many, many nice

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Speaker 1: things that people have had to buy me and not

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Speaker 1: necessarily written to me, you know, reading some of the

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Speaker 1: stuff in the press has been a real treat. And

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Speaker 1: the Nobel thing. I don't really know what next, and

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Speaker 1: I think I've talked to several previous laureates. I mean,

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Speaker 1: Princeton is great place, and there's a fair number of

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Speaker 1: the no shortage there no shortage here, right, Um. So

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Speaker 1: I was actually thinking, you know, there are only two

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Speaker 1: British born Nobel aureates in economics, and both of us

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Speaker 1: were born in Scotland, oh, you know, which is a

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Speaker 1: tiny part of the Unit Kingdom. So I don't know

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Speaker 1: what deck story is the answer. Um. I I think

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Speaker 1: it's something I'm going to have to seriously think about it. Um,

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Speaker 1: because this opens up all sorts of possibilities. And on

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Speaker 1: the other hand, I thought my life was pretty good

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Speaker 1: before this, and I have lots of good things I'm

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Speaker 1: working on, and I would really like to go on

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Speaker 1: working on those. So if I can resist all the

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Speaker 1: iron calls, I would like to do that. But maybe

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Speaker 1: some of the iron calls will turn out to be

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Speaker 1: very interesting. Yeah, and I'm interested to read further work

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Speaker 1: from you on the increase in middle aged mortality here

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Speaker 1: in the US. Two. I think that sounds really interesting

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Speaker 1: and also, as you've described it, terrifying. All Right, will

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Speaker 1: last a bit of fun and then we'll let you go. Um.

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Speaker 1: Big question. It's probably the biggest question you've been asked

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Speaker 1: since Monday. Are you on Twitter? No, there are people

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Speaker 1: pretending you have an impostor on Twitter right now. Um. Well,

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Speaker 1: I'm always on Twitter as part of my job, and well,

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Speaker 1: at least I like to say, it's part of my job.

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Speaker 1: I wanted to read out just a couple of tweets

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Speaker 1: that people wrote after the news broke. So Justin Wolf

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Speaker 1: first over at Peterson said, if there's an economist you

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Speaker 1: should want to be when you grow up, it's Angus

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Speaker 1: Deaton hardness. Isn't that nice? Yeah? And then um, another

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Speaker 1: professor over at Harvard, Angus Deaton is the obi Wan

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Speaker 1: Kenobi of economics. So you know, are you okay with

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Speaker 1: being obi Wan Kenobi or is there someone else that

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Speaker 1: you would like to be? No, I'm very happy being

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Speaker 1: who I am. And those comments um from I'm a

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Speaker 1: touch under Justin. You know, they were as wonderful as

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Speaker 1: I'm sure you would imagine they would be. These are

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Speaker 1: very serious to academics, and when they say things like that,

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Speaker 1: it really touches my heart. I personally think that you

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Speaker 1: might be more of an Alvis Dumbledore in my opinion.

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Speaker 1: You know, this great probing professor, great sense of humor,

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Speaker 1: but also cares about the well being and happiness of

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Speaker 1: both wizard and mankind. It's just my two cents. I

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Speaker 1: think I'll do it. I'll do it definitely. Well. Thank

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Speaker 1: you so much for joining us It's been such a

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Speaker 1: pleasure having you treat and thanks to all of you

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Speaker 1: for listening to Bloomberg Benchmark will be back next week

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Speaker 1: as usual, and until then you can find us on

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Speaker 1: Bloomberg dot com as well as on iTunes and pocket

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Speaker 1: casts and Stitcher, all these apps, whereas always we beg

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Speaker 1: you to rate, review and subscribe to the show. Some

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00:22:46,920 --> 00:22:49,440
Speaker 1: more listeners can find us to write us. You can

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Speaker 1: also reach us on Twitter at Daniel Malston, c at

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Speaker 1: Tory Steelwell and at at Ego Seven Star Wars metaphors

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Speaker 1: welcome and all the Harry Potter jokes we love. See

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Speaker 1: you guys next week. M