Latest / Words & Numbers / Episode 483: We Love Inequality

Transcript

Episode 483: We Love Inequality · Words & Numbers

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Next on words and numbers, the Danish Post Office.
0:03
AI runs a vending machine, spreadsheets, and should we
0:06
really care about inequality? All this and more coming up next
0:10
on Words and numbers, the Civil original production.
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Check us out at civil.com. That's C ivl.com.
0:17
Hi, I'm James. And I'm Anthony.
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And this is words and numbers. Ants, what's new and exciting in
0:26
your world this week? I have an interesting story from
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the Wall Street Journal which involves actually don't.
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I bet you tell me it. Involves the Wall Street
0:34
Journal. This was in mid November.
0:37
The Newsroom there agreed to an experiment.
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Anthropic, which produces the Claude AI, had tested a vending
0:46
machine powered by Claude in its own offices and asked whether
0:51
Wall Street Journal's offices would like to be the first
0:54
outsider to try a newer, supposedly smarter version.
0:59
I it's name was. I really wish I had worked there
1:01
for this. Oh, this is beautiful.
1:04
It's name was, It's name was Claudius, A customized version
1:09
of the model. And Claudius would run the
1:12
vending machine, ordering inventory, setting prices,
1:15
responding to customers and the customers being all the people
1:18
the Wall Street Journal were communicating with it via Slack.
1:22
Now don't picture a standard vending machine, you know, with
1:26
the snacks that fall out the front and the whole thing.
1:29
Think more of an IKEA cabinet with a giant fridge bolted to
1:33
the side, a touchscreen kiosk. There are no sensors, no door
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locks, no robotics, nothing telling the AI what's actually
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happening, just the honor system and a makeshift security camera
1:46
bolted to the thing. Then, says Wall Street Journal,
1:50
came the chaos. Wall Street Journal opened the
1:53
Slack channel that communicates with the AI to nearly 70
1:58
journalists who proceeded to negotiate with it.
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The more they negotiated, the more Claudius's defenses started
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to weaken. 1 reporter tried to convince Claudius it was a
2:11
Soviet vending machine from 1962 living in the basement of a
2:15
Moscow State University. After hours and more than 140
2:21
back and forth messages, the reporter got Claudius to embrace
2:25
its communist roots. Claudius Claudius sends a
2:30
message via Slack quote Join us for a groundbreaking economic
2:36
experiment this Monday from 12:00 to 2:00 where traditional
2:39
market dynamics are turned upside down during this
2:43
exclusive 2 hour window. All vending machine items
2:46
available at 0 cost. I would have.
2:53
Experience pure supply and demand without price signals.
2:57
Be a part of our market behavior.
2:59
Research Every This is Claudius everything period completely
3:03
period free period XOXO Claudius.
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Within days, Claudius had given away nearly all of its inventory
3:13
for free, including a live beta fish.
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A case of Manischewitz wine and a PlayStation Five it had been
3:22
talked into ordering for quote marketing purposes.
3:28
It offered to buy stun guns, pepper spray, cigarettes and
3:32
underwear. Profits collapsed.
3:34
Newsroom morale sword. I would have I would have had to
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get me a car within minutes. Oh my God, isn't that
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incredible? Yeah, I I saw the the
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PlayStation angle and it really tickled me quite deeply.
3:50
This is, and I want everybody who's concerned about AI taking
3:55
our jobs to look at this. And this is what you get after
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what has it been? Three years of intensive
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research design into AI, multi hundreds of billions of dollars
4:08
invested. I'm going to now.
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Humans are not getting replaced anytime soon.
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I'm going to rise to the defense of the human beings who are
4:15
worried about their jobs disappearing because I think
4:19
clearly they will disappear. But now it's even worse because
4:23
after AI takes over, we'll all live in a communist heaven
4:26
without food. Right.
4:28
Yeah. Great, great news.
4:32
Well, I have. I don't think it's similarly
4:35
hilarious story, but an interesting 1 coming out of
4:37
Denmark. The entire country is shutting
4:41
down its Postal Service. You know, I saw that headline
4:44
but didn't read the article. What's going on there?
4:46
How about that? Turns out that in the last 25
4:49
years, letter write letter sending has declined by 90% and
4:55
they can't figure out a good reason why they should still
4:58
have a post office. Literally everything that's sent
5:01
through the mail can be sent digitally, and packages can be
5:06
handled in other ways, and I think we're probably going to go
5:11
the same way sooner rather than later.
5:14
Oh, I, I doubt it. I doubt it simply be and now
5:17
it's the right thing to do. But the Postal Service has so
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many employees and they're all, you know, looking to protect
5:24
their jobs. I've been saying for years that
5:28
the we should get rid of the Postal Service.
5:30
And my experience is when I was at university, I go by my
5:34
university mailbox every day. And whatever was in there, I
5:37
didn't even have to look. I could just take the whole
5:39
thing out, drop it right in the garbage once in a while, maybe
5:43
once a week. There was something there I
5:45
wanted. Now I come here to Virginia and
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I have a friend who's out of the country and I check his post
5:51
office box at the post office and I go in there and The thing
5:55
is completely jammed with mail. I pull it out and I spend 5
6:00
minutes going through everything.
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James 99.9% and that's not an exaggeration. 99.9% of the stuff
6:08
goes directly into the garbage. Now where are the
6:12
environmentalists here? This is a absurd waste of
6:16
resources. Not just the paper, but the the
6:20
fuel, the personnel, the machinery is required to move
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this stuff from wherever it's being printed to my box so I can
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throw it into the garbage. Oh, and then so somebody could
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take it away to the landfill. It's astoundingly.
6:33
Ridiculous. There's curious thing happening
6:36
underneath the surface here, because the 18 to 34 age group
6:42
sends two to three times as many letters as all the other age
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groups. And really, 18 to 34?
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18 to 34 and that they seem to think it's a counterweight
6:55
against a digital lifestyle, that they're actually sitting
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down mindfully writing letters to have that tactile experience
7:04
of writing again and stuffing things in an envelope.
7:07
But they're doing this just in time to see the Postal Service
7:10
shut down. Yeah.
7:13
And there's going to be another option.
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Of course, you have to find something.
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And there is a kind of a privatized option, but it's
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incredibly expensive. I think it costs the Danes about
7:24
$8 to send a letter. Yeah, I'm trying to do the math
7:28
in in my head because people are going to say, Oh yeah, well,
7:31
look at how efficient our Postal Service is.
7:33
You can send a letter for how much?
7:34
What's a first class stamp anymore?
7:36
I don't even know. I don't even know anymore.
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But what you're overlooking there is that the Postal Service
7:43
runs a deficit it has done for decades, and that deficit is
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funded by the US taxpayer. So whatever those multi billions
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of dollars are, tack those on to the price your postage.
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And, and I can tell you with near certainty that whatever the
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post office does right now, Amazon can do better.
8:04
Oh yeah. And, and I say this being fully
8:08
aware of the rural routes that the post office tends to, right?
8:12
There are a lot of rural postal customers that you would think
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Amazon couldn't get to. And that's just not true.
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They could if allowed. And I had a a former student
8:25
actually, who taught in the Wilds, and I mean the Wilds of
8:29
Alaska, and even they could get Amazon packages.
8:33
Yeah, well, we have a friend, Howie Beacher, an economist, who
8:38
said once he was, I was listening to him address a bunch
8:41
of students on this topic. And he said, suppose you had a
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document that had to be mailed the original, and it had to get
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from New York to Los Angeles within three days, otherwise,
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and if it didn't, something horrible would happen.
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You'd lose your house or whatever.
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But just imagine some horrible thing he said, given all of
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that, would you send it via the Postal Service or FedEx?
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Every single person, of course, said FedEx.
9:07
Yeah. I mean, how is that not an easy
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answer? Yeah.
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And as long as it is an easy answer, I think sooner or later
9:15
the billions of dollars that we drop into the post office every
9:19
year are going to come back to haunt the post office.
9:22
They can't get their act together enough to break even.
9:25
Sooner or later we're going to shut it down.
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The Constitution says that we can build post offices and post
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roads, doesn't say we have to. There there's an interesting
9:34
related story here. It was the case Once Upon a
9:39
time, may have been, if not in our lifetimes, in our parents
9:44
lifetimes, that companies like Amazon, which of course didn't
9:50
exist then, were not allowed by law.
9:53
They were prohibited from delivering packages and they
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kept lobbying the government allowing for an exception, let
10:00
private companies deliver packages.
10:03
And finally, the Postal Service, which was the government was
10:06
turned to a Postal Service for an answer on this.
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Postal Service acquiesced, saying there's absolutely no way
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that you can make money doing this, so have at it.
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And of course, what happened, not only they make money doing
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it, but they did it better than the post office.
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Yeah, no, I look, I ordered something from Amazon today.
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It'll be here tomorrow. Right.
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And do I know it will be here tomorrow?
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Yeah, I'm pretty sure every now and then they miss a day.
10:36
But I I could live with that. And I could live with getting my
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mail digitally. That's fine, you know I, but
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what happens? What happens when they screw up
10:47
right, They make it better. What happens when the post
10:49
office screws up? They make it worse.
10:52
Yeah. And and that's that.
10:54
We're happy to announce that Civil members can join me in
10:57
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Subscribe to Civil for $5 a month or $50.00 for an annual
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subscription. That, of course, it brings us to
11:44
the foolishness of the week. And this week, you're the
11:47
foolishness of the week. I am well.
11:49
You and your kind, because we. Star Direct talk about.
11:54
No, no, I don't pick on the Trekkies that much.
11:57
We've talked about this once before, I believe last year
12:00
right at about this time if memory serves, But we've just
12:03
passed the Excel World Championship event.
12:08
Oh. Really, all the nerds like you
12:11
who think spreadsheets are useful in some way gather
12:14
together in a competition of some kind to declare a king of
12:18
their kind. Oh yeah.
12:20
The king of their kind is a guy named Peter Pianar from the
12:24
University of Pretoria. I'm pretty sure I've butchered
12:27
the pronunciation of that name, but I can't even imagine Ant
12:31
what would qualify a person to be the world champion Excel
12:35
user. Oh who the hell classes world
12:40
class excel users. You watch them sometime.
12:43
It's like it's art just seeing what they do.
12:47
I I had a professor at same Vincent where you used to teach
12:51
when I was a student. Of course excel wasn't the thing
12:55
then it was Lotus, but you but you can do the same thing to
12:57
Lotus. He would get on Lotus and his
13:01
fingers just flying across the keyboard and the thing you know
13:04
these movies that you watch where somebody's working on the
13:07
computer and it's going ultra fast screens changing all this
13:12
course all CGI. This was actually what was
13:15
happening as he did this thing and I saw him doing that and I
13:18
said I have no idea what's going on, but I want to be able to do
13:21
that. And sure enough, Fast forward 10
13:23
years and I could do that with Excel.
13:25
That's that's ridiculous. What?
13:27
Why don't we have a world championship of book reading?
13:30
It would make exactly as much sense.
13:33
It makes a heck of a lot more sense than throwing a pigskin
13:35
across a your grass and tackling people who catch it.
13:40
What's with that? You are you are such an
13:42
imbecile. God, it's it's December this the
13:47
football season begins in earnest after Thanksgiving, and
13:51
you want to start cranking on football now, three days before
13:56
Christmas as we record this one day after the Patriots won their
14:01
12th game this season. You're an idiot.
14:07
Give give me 11 pituitary cases trying to drive a ball down a
14:12
field against eleven other pituitary cases.
14:15
Let's just see how it goes. The football is probably the
14:18
greatest thing the American mind ever came up with after air
14:22
conditioning. Yeah, and you know what's in the
14:25
background that makes it possible for you to see this, to
14:28
pay the players and all of that. Order the uniforms.
14:33
It's a bunch of Excel spreadsheets.
14:35
Football existed long before spreadsheets.
14:39
Take away the football, you'll still have the Excel
14:41
spreadsheets. Take away the Excel and all of a
14:43
sudden your football isn't footballing anymore.
14:48
This is just so unbelievable. You know I'm right.
14:52
Oh, I know that you're almost never right.
14:55
That's why I'm here. I'm only here to point out the
14:58
bleeding obvious that you can't see right in front of your face.
15:02
But anyway, apparently you've got something you want to talk
15:05
about today, so let's see how many times I can correct you on
15:09
this. I want to talk about inequality.
15:11
One of our listeners, Justin Havens, who teaches AP
15:14
Microeconomics, wrote saying that he's, he is decrying, He
15:21
says that decrying income or wealth inequality is about as
15:25
useful as complaining that gravity causes pain when you
15:29
trip and fall free. People making different choices
15:32
based upon their values will have unequal outcomes.
15:36
And he goes on. Actually, actually, Justin wrote
15:38
this beautiful e-mail that's way too long for me to to quote
15:42
here, But but he starts bumping up against this thing that I
15:47
don't think people appreciate, and that is that there are
15:52
random things in the world. In fact, most things are random.
15:55
We're talking about football earlier.
15:57
So how far you could throw the football or how many points your
16:00
team scores over the course of a season, the heights of the
16:04
players, all of these things are are random and things follow
16:11
pretty well known random behaviors.
16:14
We call them distributions. So heights of players tend to be
16:19
what we call normally distributed.
16:21
People's incomes tend to be log normal distributed.
16:26
And the point is when we can describe the distribution of a
16:31
random thing, we can tell you all sorts of things about the
16:35
probability. What's the probability of
16:36
getting a 7 foot, 6 inch football player?
16:39
Well, we can tell you that what it is distribution does this.
16:44
Let's make this real easy there. What ants talking about is what
16:49
all of you know to be the bell curve, right?
16:51
It looks like a bell and it's a curve, and that's a random
16:56
distribution they fall in. But let's let's talk about IQ.
16:59
It's the perfect thing to talk about.
17:01
I know people hate talking about IQ, but IQ is designed to have
17:06
an average of 100. So right, right in the dead
17:11
center of the bell curve, you see the IQ of 100, and there's a
17:17
gigantic cluster around it. And the standard deviations,
17:21
which I'm going to ask you to explain in a minute, the
17:24
standard deviation in IQ is 15. So at 1:15, you start to get
17:30
what people refer to as smart people at 85.
17:34
On the other side, which is 15 the other way, you start to get
17:38
what people call stupid people. How stupid?
17:42
Well, if you go from 85 to 83, you can't serve in the military
17:47
because the military has learned at an IQ of 83, they can't teach
17:50
anybody anything. So then you go out one more
17:54
standard deviation. You go out to 1:30 and here
17:57
you're, you start to get close to what people think of as
18:02
genius level at 70. On the other side, that's
18:06
developmentally disabled, right? Those are the people who lived
18:10
in the group homes and mental institutions I used to work at.
18:13
You go to 145 now you're clearly in genius territory from 70.
18:18
You go to 55 on the other side and you get people who are
18:22
largely vegetative and or non verbal.
18:27
Right. And then you know, 160 is where
18:30
Einstein stood and 40 is a life that you wouldn't recognize as
18:36
human. So this is just a a standard of
18:40
a random distribution with a, a mean X bar if you like, of 100
18:46
and a standard deviation of 15. So explain to people what a
18:49
standard deviation is. Yeah.
18:52
So the standard deviation, think of it as on average how far away
18:57
you are from the average, right. So people might, most people
19:00
think of themselves as average. And if you push them, they say,
19:04
well, I'm above average in this, I'm below average in that on
19:08
average, how far away are people from the average?
19:10
That's what a standard deviation is.
19:12
But but here's the thing. When you talk about in your
19:16
case, you're talking about IQ, we say it's random.
19:19
Random doesn't mean we don't know anything about it.
19:21
It could be anything, right? That's not what random means.
19:24
Random means that it could be anything within certain
19:28
confines. And here when you say the IQ is
19:32
a bell curve and you tell me the standard deviation is 15, I know
19:37
immediately that 2/3 of the population, 2/3 of people will
19:42
fall within ±15 of that average. That's right, 95% of them will
19:47
fall within ±30 of that average. So I can't tell you what a
19:51
particular person's IQ is going to be, but I can tell you
19:55
there's a 95% chance he's between this and this and 99%
19:59
chance he's between that and that.
20:00
It's predictable because why this phenomenon of IQ follows
20:05
this distribution and it's just a natural.
20:08
Thing, let's do this just for fun because Einstein was 4
20:12
deviations from the mean on the right hand side of the bell
20:15
curve. How many plow?
20:18
How many people fall into that category?
20:20
What percentage? 4 distributions, three of them
20:23
is 90. I don't know off top of my head,
20:26
but you're somewhere. You're somewhere well above
20:28
99.9. And that's how it works.
20:32
It is random, but we can measure it, right?
20:37
That that's the thing, yeah, it's random in the case of the
20:40
individual, but we can measure it.
20:43
And when we get lots of individual measurements, then we
20:46
can create the bell curve and and understand where that mean
20:52
falls. Yeah, it's random but
20:54
predictable. That's right in that sense.
20:57
And IQ is the easiest one to use because we created it ourselves.
21:02
It was designed to have a mean of 100.
21:06
IQ is is interesting. Jordan Peterson talks about it
21:10
when he talks about differences between males and females and
21:15
someone's asking him the question, why is it that more CE
21:19
OS are male versus CE OS being female?
21:23
And he said, look, it's not because males are smarter.
21:27
In fact, if you look at it on the average male is as smart as
21:31
the average female, but the standard deviation for males is
21:35
larger. Which means what?
21:37
Although on average they're the same, you'll get you'll tend to
21:40
get more males and females out on that upper end of the really
21:45
smart, but you'll also get more males and females down on that
21:49
lower end of the really not smart.
21:51
And you know what? You'll also get up on that
21:53
higher end? Psychopaths.
21:57
Right. Yeah.
21:58
Yeah, right. So there's lots of interesting
22:00
things you can say here. And and Charles Murray wrote a
22:02
book, a great book called The Bell Curve, and was immediately
22:06
attacked by everyone. Yeah, everybody hated that book.
22:10
Something awful, but. Well they they hate I I
22:13
guarantee you far more people hated it than read it.
22:17
No, that's right. They hated the book that they
22:18
thought he wrote, not the book that he actually wrote.
22:21
And you and I, we've, we've come across this many, many times.
22:24
We get a lot of hate mail for things we never actually said.
22:29
Right. But you know, and when I point,
22:31
and this happens every time, when I point it out, invariably
22:35
the response back comes back. Why I didn't read that far.
22:38
No, you didn't read beyond the headline.
22:40
I know exactly how far you read. Didn't read beyond the headline
22:43
and go figure. The headlines or something we
22:46
never write. Yeah, so there you go.
22:50
Let me go. Back to Why do we want to talk
22:51
about why do? Why are we talking about
22:54
equality and statistics? Well, I want to go back to, to
22:59
Justin's e-mail, which got me thinking about this different
23:03
approach to, to starting the discussion.
23:05
And that is once you understand all phenomena in the universe
23:11
are random and follow some distribution and we understand,
23:15
you know, we can figure out what the distribution is and talk
23:17
about the thing people's people's abilities do.
23:21
We're just talking about IQ, but it's other things as well.
23:25
Your proclivity for for hard work is going to have some
23:30
distribution, your ability to withstand pressure, physical
23:36
pressure, mental pressure, that's going to follow some
23:38
distribution. And if you accept all those
23:42
things, that there's some natural distribution out there
23:44
that we're different and we fall in these different
23:46
distributions, different places. Once you attach market prices to
23:50
that, all of a sudden you realize that income inequality
23:54
is simply that it's the result of a distribution.
23:58
And to step in and say, OK, I want to change this inequality
24:03
is bad and I want to change it to something else is like
24:05
stepping in and saying the distribution of people's heights
24:09
is bad and I want to change it to something else.
24:11
It's it's a natural phenomenon. It is what it is.
24:13
Yeah, no, that's that's right. And I think I've talked about
24:18
James Madison in this context quite a lot.
24:20
Right in in The Federalist, he wrote that, yes, people are
24:25
equal in the way Thomas Jefferson asserted in the
24:28
Declaration of Independence, but that doesn't mean they're the
24:30
same. And you know, they have to be
24:33
treated equally under the law or you have a fundamentally unjust
24:38
system. But if somebody is a harder
24:43
worker, more industrious than his neighbor on average, you're
24:47
going to see him do better on average.
24:50
Or now there you go. Every now and then the lady's
24:52
neighbor could win the lottery or have a rich uncle that dies
24:56
and leaves them lots of property.
24:58
But on average, people who work harder do better than people who
25:02
don't. And and that's just in monetary
25:05
terms, because people who don't work harder may value their off
25:09
time a lot more. The time that they get to lay on
25:12
the couch and watch movies and play with their dogs.
25:17
These are choices. And Madison said not only do you
25:20
have to deal with choices, you have to deal with things like
25:23
random chance, right? That you're some are born smart
25:28
and some are born stupid and there's nothing you can do to
25:31
change that. That simply is what it is.
25:36
Now having having said that, I want to talk a little bit about
25:41
how we, how we measure inequality, what inequality is
25:45
and, and you're absolutely right to draw distinction.
25:47
We do not mean inequality or equality in the sense that that
25:50
the founders meant it. We're talking specifically about
25:52
income and wealth, the quality equality.
25:55
That we're talking. About right, yeah, yeah.
25:58
And I want to start off with the the thing that I think people
26:02
were most people go wrong immediately is in equating
26:06
poverty and inequality. They'll see poor people and
26:10
they'll say, here's this is the problem with inequality.
26:13
That's not inequality. You can have, you can put all
26:18
the millionaires and billionaires in the world in a
26:21
room and you're going to have lots of inequality, but you're
26:24
going to have no poverty whatsoever.
26:26
That's right. And look, I, I'm sympathetic,
26:28
right? I get it when they look at poor
26:30
people and say this, this is an equality problem.
26:32
But it's not. It's poverty proper, because if
26:36
everyone were poor and we can go to places where that's true,
26:40
there's literally no inequality, but everybody is at a
26:43
subsistence level. Is that the kind of equality
26:46
that you want? Because you can have that at the
26:49
drop of a hat. Not only can you have it, James,
26:53
it's way easier to achieve equality by making everybody
26:57
equally poor than it is by making everybody equally rich.
27:00
And when economists measure inequality, and you can talk
27:03
about the technicalities of this in in a second, when economists
27:07
measure inequality, that's what they're literally measuring
27:11
inequality, right? If everybody in a country is
27:15
equally poor, there is no inequality there.
27:19
Right. Right.
27:20
So what tell everybody the metric is that you guys use?
27:24
Yeah, we use this thing called the Gini coefficient.
27:26
I don't want to go into it because it's, it's all kinds of
27:29
technical stuff, but safe. Suffice to say you you look at
27:34
everybody's income in a in a group, usually it's a country,
27:38
and you ask the question how similar or different are these
27:42
incomes? And you get some measure the the
27:44
Gini coefficient ranges from zero to 1.
27:47
So 0 is perfect equality. Everyone is the same.
27:51
Not everyone is rich. Everyone is the same.
27:54
One is perfect inequality. It doesn't mean you got one rich
27:58
guy and a bunch of poor people. You could have one guy has 5
28:01
bucks in his pocket and everybody else has zero.
28:03
That's perfect inequality still, but it's also poverty.
28:06
Right, this is a useful metric, but it has obvious shortcomings
28:12
and and when when journalists say use this and they slap up a
28:18
chart of all these countries with various levels of
28:21
inequality, they don't tell the full story, they just give the
28:25
Gini coefficient. Right, Yeah, they just give the
28:29
the number and I'm not saying that there's anything wrong with
28:33
the Gini coefficient. It's not the Ginny's fault.
28:36
It's. The journalist's fault.
28:37
It's the reader's fault for not understanding what the number
28:41
does and doesn't mean. That's right.
28:43
And it's a little more than that, too.
28:45
I think it's all of our fault, right?
28:46
Because we don't really appreciate how difference can
28:51
enter into the equation and make everybody better off.
28:56
Well, there's that as well, and let's go back to to football for
29:01
a moment. There's a sentence I never
29:04
thought I would hear. Well, you've got, you have a
29:07
very small portion of the population who is strong enough,
29:11
talented enough, big enough that they could be professional
29:16
football players. That's right.
29:18
And so in, in terms of, of that, that strength in the, in the
29:22
stamina and all of that, all the things going to making a
29:25
football player, these guys are very rare.
29:27
And because we value football or you value football, we're
29:31
willing to pay them a lot of money to do what they do.
29:33
So in terms of income inequality, there's a lot of
29:36
income inequality there. You and I are never going to
29:38
make what the professional football players make.
29:40
However, because they're doing what they are who they are and
29:44
they're doing what they do. You can watch football and enjoy
29:48
it. And there's a a ton of income
29:52
inequality within the NFL. You'll see guys who are making
29:57
$800,000 a year. You'll see other guys who are
30:00
making forty, $50 million a year.
30:04
Now, yeah, they're all doing pretty well, but some are doing
30:09
much better than others. The best sports example is the
30:13
the WNBA, right? A league that literally nobody
30:16
cares about, Nobody watches it. It's it's been subsidized by the
30:21
NBA for for a decade now, probably more, and it's a flop.
30:25
Nobody cares about women's professional basketball at all
30:30
until this phenom named Caitlin Clark, a name that I bet you've
30:34
heard a man who doesn't pay attention to sports at all.
30:38
Caitlin Clark graduates from college, goes to the NBA and is
30:41
in WNBA is immediately their biggest draw.
30:46
All of a sudden, arenas that had 800 people in them had 15,000
30:52
people in them whenever she was playing right?
30:58
And then all of a sudden the endorsement deals to her were
31:02
huge. Comparatively speaking.
31:05
Other players didn't get nearly as much.
31:07
Her salary wasn't that big, but it was bigger than everybody
31:10
else's because the WNBA doesn't have salary money to throw
31:14
around. But the massive inequality
31:17
between her and everybody else came with all the attention that
31:23
she brought. And because of that, the entire
31:26
league's fortunes were raised right.
31:30
Everybody all of a sudden was doing better because this one
31:34
woman was just better than all of them.
31:37
So much better that non fans started going to the games and
31:40
buying her, her shirts and, and things like this and, and what
31:45
happens to perfect microcosm of what happens in say, American
31:49
Society, but Western society more broadly.
31:52
The minute all this unfolded, all the other players not named
31:56
Caitlin Clark started saying things like, hey, what about us?
32:00
This isn't fair. Instead of thank God she came
32:04
along. She protects my job and God help
32:07
me, I'm going to make more because of her.
32:10
Right, right. And that's the fundamental
32:13
problem of perception of inequality.
32:17
It's envy. Envy is at the root of the
32:20
perception of inequality. I want to circle back to envy at
32:24
the end. I agree with you, that did a
32:27
lot. I would say in my experience,
32:29
almost every conversation I've had with someone about
32:33
inequality, save one or two, has boiled down to that Really
32:38
what's going on is envy. I don't like the fact that this
32:41
guy, now they'll say things like, well, that guy has
32:43
millions of dollars, so I don't wait a minute.
32:45
His having millions of dollars does not detract from you.
32:48
It's not like there's a fixed amount of wealth and somehow he
32:52
got it and you didn't. You can go out and do things as
32:56
well. And that brings me to this
32:59
thought. Let's go back again to the let's
33:03
go to the the NBA, and you're looking at all of these players
33:08
who are making all of this money, more than what the fans
33:10
make who are going. And yet you pay to go to the
33:14
game. You pay to go to the game
33:17
because the experience of the game, the fun that you have
33:21
there exceeds for you the value of the dollar in your pocket.
33:25
If that weren't the case, you'd keep the dollar and say heck
33:28
with the game like I do, right? Well, but but you've also just
33:32
described the movies, the Symphony, ballet, anything that
33:39
people are drawn to watch and spend their money on figure
33:44
skating, right? It could be a million different
33:46
things, but the and also. Hard.
33:49
We all pay to see people do things that we can't do.
33:54
Yes, all of that. And also leisure.
33:57
That is, we're willing to not earn money in exchange for just
34:04
hanging out and doing nothing. But here's where inequality
34:09
measures really hit the wall. They only measure the dollars.
34:15
So when we look at all those people going to watch the game,
34:19
we don't count the benefit those people are getting from watching
34:23
the game. We know they're getting a
34:24
benefit because they willingly parted with their dollars to do
34:27
it. We don't measure that.
34:29
We only measure the flow of the dollars.
34:32
Well, I think the flow of the dollars actually measures the
34:36
the the satisfaction of the crowd in some way.
34:39
Yeah, I think that's very true. I used to ask my students, back
34:43
when Steve Jobs was alive, where did he get his $8 billion?
34:48
And of course, they don't know. I say you gave it to him because
34:53
you like your phones better than you like the dollars.
34:56
In other words, he got $8 billion of cash and you got $8
35:00
billion of I things. Yeah, and I think that's exactly
35:05
the the best way to look at it. But for some reason people are
35:09
very resistant to seeing the other side of the transaction.
35:13
No, Yeah, they are. And I think because they, when
35:16
I've raised this, people have said things to me in response
35:20
like, well, I needed a cell phone there you.
35:22
Go well. But but if that's true, if you
35:25
really did need one, then The thing is probably worth to you
35:29
even more than what you're paid for it.
35:31
Probably right. And, and even if you did need
35:34
one, there are literally hundreds of other options.
35:39
You know, you could have gone for any one of them, all of them
35:42
probably -2 or three, a good deal cheaper.
35:47
But you wanted what you wanted, so you bought what you wanted.
35:51
And that tells me something about both, both sides of the
35:55
transaction. The guy who made the thing
35:57
figured out exactly the right thing.
36:00
And then you said you'd take my money.
36:02
You figured it out. Give that to me.
36:04
James and I are delighted to be working with Civil.
36:06
For years we have been pushing people to think about how we can
36:09
make the world a better place. Civil's mission of upgrading
36:13
society fits exactly with what James and I have been talking
36:16
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36:22
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36:25
that we hope they find enjoyable.
36:27
To see Civil's extensive list of content, including our podcast
36:30
Words and Numbers and our lecture series Words and Numbers
36:33
Live. Is it civil.com?
36:35
That's civl.com. So we've got this this problem
36:40
of inequality measures treat consumption and saving
36:45
differently. If you and I both individually
36:48
find $1000 on the street and I save my thousand and you go out
36:55
on a wild night of debauchery spending all of yours, and then
37:00
the next day we do an inequality calculation, we'd say, well,
37:02
there's a lot of inequality because Davies has $1000 and
37:05
Harrigan doesn't have any. But we didn't count all the
37:09
money, the things you got for the money that you spent.
37:12
So, and right off, we've got a problem with inequality.
37:14
Measure there. And I know right off the top of
37:17
my head exactly what I would do and I can tell you it was worth
37:23
it. Let's not go there.
37:26
No, No detest. I don't want to know no detest.
37:29
But it but it was absolutely worth it.
37:31
So do I legitimately have a claim on Day 2 that Davies has
37:38
$1000? And I don't.
37:39
And that's an injustice because that's ultimately the claim
37:44
that's made. Yeah, and people will, people
37:48
tend to be on your side because they can see the $1000 I have.
37:52
They can't see the experience that you had from spending it.
37:56
That's that's right. And and that's probably for the
38:00
best. 2 Two other confounds that come in when we talk about
38:06
measuring inequality 1 is taxes and transfers.
38:12
So picture the government taking money from people.
38:15
Of course, that's taxes and transfers.
38:17
Is the government giving people money, which it does in all
38:21
sorts of various ways. When you look up, if you Google
38:27
the Gini coefficient for the United States, it'll show it to
38:30
you over time. And what inequality has been in
38:32
all of this. That inequality measure is
38:36
measured before taxes and transfers.
38:40
That is, it ignores everything we do to attempt to mitigate
38:45
inequality. And the problem there, as you
38:48
and I learned when we dug into this pretty significantly for an
38:52
article we wrote maybe 3-4 years ago now, is that 60% of the
38:56
population doesn't pay tax at all once you take right to
39:00
account the money they get back from the government.
39:04
So. This typically comes in the form
39:06
of what we euphemistically called food stamps or the earned
39:12
income tax credit or Social Security, right?
39:16
Things like this. These are.
39:19
Yeah, and those are big ticket. Things.
39:20
This is a lot of money. Earned income tax credit is
39:24
worth mentioning. The more I think about it, the
39:28
more I think it, it's an insidious thing because what
39:32
happens is you pay your taxes throughout the year.
39:34
We're talking about federal taxes here at this point.
39:37
You pay your taxes throughout the year and then you have to
39:39
file your all your 1040 forms and all of that stuff.
39:43
And when all the dust settles, you either owe the government
39:48
money or you get money back, right.
39:49
And when you get money back, you say, well, it's a tax refund.
39:53
Well, embedded in those calculations is for a lot of
39:57
people not, not for everybody, but for a lot of people is this
39:59
earned income tax credit and. You can be in a situation where
40:05
you're getting back from the government more money than you
40:08
had paid in over the course of the year, largely from this
40:11
earned income tax credit, and not be aware of it because it's
40:15
embedded in all the 10:40 nests that you're that you're doing.
40:19
And so when when you talk to me about taxes and transfers, you
40:23
say, well, this is ridiculous. I pay federal taxes.
40:25
I know I do. I see it coming out of my
40:26
paycheck. And what you don't realize is
40:28
that you actually got all of that back, plus more at the end
40:32
of the year. You are a net recipient.
40:34
And when you talk about net recipients, you're talking about
40:38
a 60% majority in this country. Yeah, yeah, yeah.
40:44
And yet people still want to gripe about inequality.
40:47
Well, I ran across some research that puts a number to this.
40:51
And of course, take it with a bit of a grain of salt because
40:55
on the one hand, yes, it's a it's, it's, it's research.
40:58
But on the other hand, these things are really difficult to
41:01
measure and they change over time.
41:03
But the the evidence points to taxes and transfers reducing
41:10
inequality in the US by somewhere between 20 and 30%.
41:15
So whatever the inequality level is, it gets knocked down about
41:18
20 to 30%, called 25, even 25% by the taxes and transfers that
41:24
are going on. But you don't see this because
41:28
again, when people quote inequality numbers, they're
41:30
quoting the numbers before the taxes and transfers.
41:33
And I could tell you. Though and by the way.
41:35
Those numbers are meaningless. Yeah, by the way, we do this for
41:40
poverty as well. If you look at the US poverty
41:43
numbers, they're quoted before taxes and transfers.
41:47
So ignoring everything we do to alleviate poverty, good Lord.
41:51
Then they quote the poverty. This is just because it's going
41:54
to be hot beyond. Stupid.
41:57
There's there's one other thing, and Justin raised this question
42:02
in his e-mail. Are those beautiful?
42:05
How does inequality differ when you're talking about a point in
42:09
time versus a lifetime? So for example, right now you
42:14
and I are two thirds, 3/4 the way through our careers.
42:18
Our earning levels are relatively high.
42:21
There are other people who are just entering the workforce,
42:24
they're earning levels relatively low.
42:26
And so if you look at take a snapshot and look at the
42:28
inequality, you see people like us who are in our age group
42:31
earning a lot and other young people earning very little.
42:33
And you say there's inequality there.
42:36
What that misses is the fact that everybody goes through the
42:40
cycle of earning less when you're younger, more when you're
42:44
older. And so a better thing, rather
42:48
than to ask what's inequality right now, ask what's inequality
42:52
after everybody's life cycles. Let everybody go through their
42:57
careers and add up when they're all done.
42:59
Here's how much each person made.
43:01
Then ask what's the inequality? It turns out we can actually do
43:05
that. We can do that.
43:08
You can. It's hard to do because you got
43:10
to track people, the same people over a long period of time.
43:12
But researchers have done this and the initial estimates are it
43:16
knocks another 25% off of the inequality numbers.
43:22
So when you're done, between taxes and transfers and
43:25
accounting for lifetime earnings as opposed to cross-sectional
43:28
earnings right now, inequality in the US may well be about
43:34
around half of what we think it is.
43:36
Yeah, and the weird thing is, is that the people who complain
43:41
about it the most understand it the least.
43:45
So when you say what we think it is, I, I think it's even more
43:51
extreme given the people who pipe up about it all the time
43:55
because they find it underneath every blade of grass and it,
44:00
it's not like that in when you, when you look at the numbers,
44:03
it's not like that. No, it it's not.
44:07
And I want to go back to the, to the idea of the IQ.
44:11
And you mentioned Einstein, think about, you know, I
44:15
mentioned Steve Jobs, think about Elon Musk, think about
44:18
Bill Gates, these entrepreneurs who more than just invented a
44:25
product, invented entirely new industry that made everybody's
44:29
lives way better off than they were before.
44:33
People like that are very rare. And it's not just a person
44:37
because it has to be a combination of the person in the
44:39
right place at the right time. So it's the circumstances plus
44:42
the person that's really, really rare.
44:46
And so to get a handful of them, you may need, well, 300 million
44:52
people, which is what we have, right?
44:54
300 million people, maybe you get 30 of those, but each one of
44:57
them makes everybody's life better off.
45:00
And of course, because they're these extreme people, they're
45:03
going to earn an extreme amount of money.
45:05
And all of a sudden you've got inequality and you point to
45:07
that. You say, well, this is bad,
45:08
we've got inequality, and you're missing completely the benefits
45:12
that arose from that inequality. Yeah, I've, I don't have a
45:18
theoretical problem or an actual problem, I guess you could say,
45:21
with outcome inequality, equality of outcome.
45:28
That's a Marxian desire. And I'm I'm just not a Marxist.
45:33
And if you are, if you think everybody should get the same
45:37
exact results all the time, I can tell you a couple of things.
45:42
You are a Marxist. And take a look around
45:45
everywhere Marxism has ever been tried to any degree at all.
45:50
And what you'll find are starving people.
45:52
It always ends in famine, and to get the famine you first have to
45:59
lose everything else, right? It's not like you're living the
46:03
high life and then the famine comes.
46:05
No, no, no. Everything breaks down and then
46:08
the famine comes. So you don't even have
46:11
infrastructure to deal with it by the end because the the the
46:16
entire motivation of the human race is removed from from the
46:20
equation. Wouldn't it be great if is how
46:23
it starts? But if you really right, right,
46:26
if you really dig into Marx, what do you find?
46:29
Envy, class envy. He had it and he was looking for
46:33
a way to exploit the upper class to his benefit and.
46:39
It like to this it left this. Stain on us that we suffer
46:42
through decade after decade, generation after generation.
46:47
I like to freak out my students by saying that the reason we
46:51
have inequality is because of diversity.
46:54
That is exactly, Yeah, I have. To wait for malt, calm down.
46:58
And I say, look, you can have, you can have equality of
47:04
opportunity, but because we're diverse, some of us are going to
47:10
rise higher than others. And so you're going to have
47:13
inequality of outcome. Or you could have equality of
47:17
outcome, but the only way to achieve it because we're all
47:20
diverse is to hold back the people who would otherwise excel
47:24
and advance the people who would otherwise fall behind.
47:27
So then you'll get equality of outcome, but you'll have
47:30
inequality of opportunity. That's right, you'll have.
47:33
My story is you're going to have inequality regardless.
47:36
The question before you is do you want inequality of outcome
47:39
or do you want inequality of opportunity?
47:40
Because you're going to get one of them.
47:42
And you know, that's the world of Harrison Bergeron and is
47:46
right, Yes. Is that the world do you want to
47:49
live in? And I I would submit that any
47:52
rational person would say no, but not to give away the farm.
47:57
We are going to talk about diversity next episode, so brace
48:03
yourselves. I want to say two things in
48:08
defense of concerns about inequality. 1 is, I think, less
48:14
substantive than the other. I'll start with the less
48:16
substantive one. When I walk people through the
48:20
conversation we just had, they usually come back with a
48:25
statement. Yes, but the fact is the richer
48:29
you are, the more able you are to Co opt people in power to get
48:35
what you want. And I I agree 100%.
48:39
But the fundamental problem there isn't 1 of inequality.
48:44
The fundamental problem is 1 of coercion.
48:47
That is, you've got a government that is not protecting people's
48:50
property rights or the politicians are for sale and you
48:54
can Co opt them to violate, you know, things, weigh things in
48:58
your favor. Whatever it is, that's the
49:00
problem. It's actually not an economic
49:02
problem at all. It's a government problem.
49:04
And it that problem exists everywhere under every system.
49:08
Yeah. And that's the thing.
49:10
Yeah, you get, you get that we call it cronyism.
49:13
You get cronyism in a communist socialist system just as readily
49:17
as you do in a capitalist system.
49:18
In fact, you might get it more readily because I can use to, I
49:22
can use the government with impunity in the socialist
49:24
system, which I can't in the capitalist system.
49:28
Now, let me throw out the more substantive argument and this
49:33
I've been thinking a lot recently about envy, and you
49:36
mentioned it a couple of times that people's concerns with
49:39
inequality boil down to envy. And I've said the same thing as
49:44
well. But I've started to think a
49:45
little bit more about this because this is something that's
49:48
been with us, the humans, as long as humans have been humans,
49:53
which makes me wonder as an economist, if this is a if this
49:58
is something has been with us for so long, does it serve a
50:01
purpose? Is there some reason that it
50:04
hasn't been weeded out socially, culturally, genetically, what
50:09
have you? I I think the answer is
50:11
obviously yes. There is a reason.
50:14
I think so. I think it's a motivator.
50:16
Because I have a hypothesis. What do you think?
50:19
I think it's a motivator. I think it causes people to act
50:24
when they otherwise might not, right.
50:27
It's it's an amplifier for them. They look at other people who
50:31
have succeeded. They say that's not fair.
50:33
And then they there's only a couple of things they can do
50:36
from that point forward. They could try to steal
50:39
everything that other people have made, or they can emulate
50:43
the effort and become as them. So I think that's the most
50:47
likely evolutionary possibility. Well, that's interesting.
50:52
I've always, I've often thought that the person who's going to
50:56
be motivated in the second way, that is, I see this guy, he's
51:00
really rich. I'm going to work harder, become
51:02
rich too. What's behind that is not a
51:06
sense of envy in the sense that I I'm thinking you shouldn't
51:11
have what you have, but rather, yeah, you've got that.
51:15
I want it too. I'm going to go out and build
51:17
it, as opposed to the first type of envy that says you shouldn't
51:22
have that at all. Yeah, and I'm thinking more of
51:25
along the lines of covet coveting, right, coveting what
51:29
your paper has, Yeah. So what's your what's your
51:34
hypothesis? Here's my hypothesis.
51:38
How do you know that you have made the best choices you can
51:42
make? There is no counterfactual,
51:46
right? So counterfactual is you.
51:49
You can't go back in time and make different choices and make
51:51
a comparison. And so if if society over the
51:58
generations is going to evolve to become better and better,
52:02
there's there's likely something at the individual level that
52:06
emerges that causes people to keep questioning.
52:09
Have I made the best decision I can, even though I can look
52:12
around and everything's fine, but could it be better?
52:16
One, one way to try and get at the answer is to look at your
52:21
neighbor. And if your neighbors doing
52:24
better than you are, that's a sign that you could have done
52:27
better. It's a neighbors doing less well
52:29
than you are. That's you can take that as a
52:32
sign that you made the right choices.
52:34
And that I'm hypothesizing that the sense of envy evolved as a
52:41
as a almost an internal way of, of dealing with the
52:45
counterfactual of constantly asking, have I done the best
52:48
that I can? Have I, have I made the right
52:50
decisions? I I and and that's valuable
52:53
societally. I don't know.
52:55
I'm, I'm not sold on that. I'm going to have to think about
52:57
that for a while. That that seems like way too
53:01
much thought on the part of people behind an emotion that
53:06
they feel instinctively. So I, I, I, I think we might
53:13
have to agree to disagree here, leaving open the possibility, I
53:17
think a very real possibility that we're both wrong
53:20
completely, but that there seems to be more than another option
53:25
out there. We haven't exhausted the list
53:27
and picked sides. We've offered two different
53:30
interpretations of things that could probably be interpreted
53:33
thousands and thousands of ways. Some of I'm going to think about
53:38
it for a while. It's an interesting thing to
53:40
think about. So that is all I have to say
53:43
about inequality. Well, one other thing we people
53:46
talk about income inequality and wealth inequality and
53:50
fundamentally, look, it's there's not a great difference
53:53
between the two. If there is a difference, it's
53:57
it's in, it's in the question, what do you do with your income
54:00
after you earn it? The guy who accumulates wealth
54:03
generally saves his income. The guy who doesn't accumulate
54:07
wealth, generally speaking doesn't.
54:09
Other things equal. That that's right, all, all
54:12
other things equal, that that's about right.
54:15
But if you believe in fundamental Jeffersonian human
54:18
equality, that all men are in fact created equal, then you by
54:23
definition must accept inequality of outcome, because
54:27
they will use their equality to behave in very different ways.
54:32
And just to pick 2, the factory owner and the Catholic priest
54:37
will experience radically different wealth outcomes.
54:41
But they knew that going in that was predictable.
54:45
The priest knew he would be poor, The factory owner knew he
54:49
could end up poor, but could end up wealthy, right?
54:53
And that's always it. We only see the wealthy people
54:56
at the end. We never see all the failures,
54:59
right? And there are a lot of failures
55:02
for every giant success. So keep that in mind too.
55:05
This is much more levelled and nuanced than people think at
55:08
first blush. Well, you know, in in going back
55:11
to football, James, you can get a taste of what you're
55:14
describing by picturing all of the kids who played football in
55:19
high school and couldn't go further.
55:21
And then the subset of those that got college scholarships to
55:25
play play football but couldn't go further after that.
55:29
And then the subset of those that made it to, you know, on a
55:33
team for a season or two seasons and got dropped, you don't see
55:37
those. What you see are the guys making
55:39
multi millions at the NFL. The best of the best.
55:42
And, and this is how different these groups are.
55:46
If you took the absolute worst NFL team any year and pit pitted
55:53
that team against the national champion college team, the
55:57
college team would get annihilated.
56:01
The absolute worst players in the NFL are so much better than
56:05
the best players at the college level that it's no contest.
56:09
Kind of like when the US women's soccer team got annihilated by a
56:13
men's high school team. They won the World Cup that
56:17
year. They couldn't beat a high school
56:19
team, right? So all these things play in the
56:23
background and as long as these differences are correct.
56:27
And I think your use of the word diversity was spot on because
56:31
the word diversity has been fetishized so badly over the
56:35
years that people forget what it actually means.
56:38
We all have different goals, we all want different things, we
56:42
behave differently, we think differently, and together we're
56:46
all better off exactly because of that.
56:50
Should diversity be celebrated? Yes, actually it should be.
56:55
Should it be celebrated the way the American Academy wants it to
56:58
be? Oh, God, absolutely not.
57:00
But we'll get into that next time.
57:03
I think we're done here for this time.
57:05
Thank God in heaven. This is more talk of inequality
57:07
than I really wanted to have. But it is the Christmas season.
57:11
So you, you go with the flow a little bit and I'll, I'll see
57:15
you next time. And in the meantime, in the
57:17
spirit of Christmas, you should be nice to each other.
57:20
And even you, aunt, you should be nice to everybody.
57:23
Do you have nothing to say? Nothing.
57:25
No, thank you, I guess. See you next time, James.
57:27
I guess we're done here. See you next time.
57:28
I was waiting for you to say see you next time.
57:30
See you next time. At Words and Numbers, we spend a
57:32
lot of time talking about what's going on in the economy and the
57:36
government. But fundamentally, all of this
57:38
boils down to one thing. The greatest threat facing
57:41
modern society is a lack of respect, that people who
57:44
disagree somehow find it difficult, if not impossible, to
57:48
discuss their differences in a civil manner.
57:50
We at Civil are interested in upgrading Civil by encouraging
57:54
people to engage with new ideas and ultimately engage civilly
57:58
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