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PROFESSOR: So I guess maybe the
lecture today is the one

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00:00:33,350 --> 00:00:38,860
that is going to have the
findings which in a sense are

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00:00:38,860 --> 00:00:47,110
the most surprising to me and
probably the most, let's say,

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unconventional or that would
upset the most people.

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None of these studies
are mine.

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They're all studies
by other people.

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But I think that together
they paint a

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somewhat surprising picture.

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00:01:03,585 --> 00:01:05,920
A small family is
a happy family.

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This is actually a bag of rice
that someone took a picture of

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with the slogan, "A Small Family
is a Happy Family"

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painted on it.

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That's a picture from
someone's travel.

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So most international public
policy has been predicated on

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00:01:26,720 --> 00:01:29,535
this idea that large families
are bad, and particularly bad

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00:01:29,535 --> 00:01:30,730
for children.

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00:01:30,730 --> 00:01:34,100
And the second one is this
one, that poor people are

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unable to control
their fertility.

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So that's kind of some of this
maybe slightly despising view

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00:01:43,200 --> 00:01:45,230
about what the poor can do.

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00:01:45,230 --> 00:01:49,970
Here you have the social worker
coming to the very

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00:01:49,970 --> 00:01:53,340
poor, dilapidated house with a
large number of children and

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the mom saying, but I take the
pill every time and become

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pregnant, and it doesn't help.

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So that seems to me like a
pretty good summary of where a

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lot of people are explicitly
or implicitly.

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00:02:05,660 --> 00:02:10,830
And what I'm going to argue
today, and not on the basis of

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00:02:10,830 --> 00:02:13,430
what I've done but on the basis
of a lot of work that

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00:02:13,430 --> 00:02:16,960
I've accumulated, is that both
of these statements are

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00:02:16,960 --> 00:02:21,485
actually wrong, not
mostly wrong.

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00:02:21,485 --> 00:02:22,895
But let's start with
the beginning.

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00:02:25,910 --> 00:02:26,800
Why does it matter?

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00:02:26,800 --> 00:02:28,520
Why do we spend time
on this issue?

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00:02:28,520 --> 00:02:32,750
And why is it important that
people get it wrong and to try

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00:02:32,750 --> 00:02:34,530
and get it right instead?

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00:02:34,530 --> 00:02:36,690
It's because these
kind of views

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00:02:36,690 --> 00:02:39,970
actually influence policies.

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00:02:39,970 --> 00:02:44,500
So the first example is the
sterilization policy during

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the emergency period in India.

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So what happened during
this period?

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What was the story?

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AUDIENCE: There was this huge
campaign for sterilization.

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And basically there were lots
of incentives or hand

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00:02:59,279 --> 00:03:00,983
[INAUDIBLE] provided
to ensure that

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00:03:00,983 --> 00:03:03,920
people met certain quotas.

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Like, various policies, Muslim
people were taken into jail

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and then forced to
be sterilized.

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It was just a very harsh
technique to achieve a quota.

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PROFESSOR: Exactly.

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There was a huge, very fast
campaign for sterilization,

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which was very much delivered
from the top.

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7 million people got sterilized
in a very short

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period of time.

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If you're interested in reading
an account of the

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emergency period in India,
there's actually a novel

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called The Fine Balance
by Rohinton Mistry.

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It's a whole kind of full
spectrum novel about the

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00:03:41,640 --> 00:03:46,030
emergency period, has some
horrific descriptions of those

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camps which are based on some
of the accounts that people

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have given.

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So some of this, of course, is
people were given incentives

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to be sterilized.

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But people were also sometimes
given offers that they could

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not reject.

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So there was sterilization
that was not voluntary.

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And, for example, people
traveling on trains without

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00:04:10,620 --> 00:04:14,190
tickets, which was a widely
accepted practice at the time,

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were all rounded up
and say you get

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sterilized now or else.

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Widely unpopular policy,
as you can imagine.

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Then when Indira Gandhi called
an election towards the end of

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emergency, she was convinced
she would win the election

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partly because that's the
problem of being all alone in

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power, that you don't
understand.

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No one gives you the real view
of what is going on.

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00:04:41,840 --> 00:04:45,200
And she did lose the election
pretty badly.

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00:04:45,200 --> 00:04:49,280
And it is, of course, hard to
tell but it is widely believed

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that sterilization policy was
part of the reason why she

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00:04:54,570 --> 00:04:56,160
lost the election.

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And, in fact, there was this
slogan which was based on a

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00:05:01,030 --> 00:05:05,490
pun in India, kick down or kick
out Indira and save your

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00:05:05,490 --> 00:05:07,860
penis, which is based
on the phonic

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analogy between the two.

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So that was a success in very
immediate terms and a very big

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failure in a longer sense
because people in the rural

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areas are pretty reluctant of
having anything to do with

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family planning.

95
00:05:28,180 --> 00:05:32,210
For example, there is this very
safe way of providing

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family planning, which
is an injection that

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00:05:35,410 --> 00:05:37,350
is valid for 3 months.

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And that's very convenient
because then you can

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00:05:39,910 --> 00:05:40,690
forget about it.

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00:05:40,690 --> 00:05:44,120
You don't have to remember to
take your pill every day.

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It's not very healthy, which is
why people don't prescribe

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it so much.

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But it does have the convenience
of being

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very easy to use.

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And people are really not a big
fan of it in India partly

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00:05:54,480 --> 00:05:57,240
because they are wondering if
it's some roundabout way to

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00:05:57,240 --> 00:05:59,640
actually sterilize them.

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00:05:59,640 --> 00:06:02,630
Worse than that, and we
discussed that in the context

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00:06:02,630 --> 00:06:08,075
of immunization, people feel
that other things could also

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00:06:08,075 --> 00:06:10,240
be some roundabout way to
try to sterilize them.

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00:06:10,240 --> 00:06:13,670
And in particular because
Muslims were certainly a group

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00:06:13,670 --> 00:06:18,145
that was particularly targeted
during the sterilization wave

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00:06:18,145 --> 00:06:22,780
in the emergency, Muslims
sometimes refuse to take even

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00:06:22,780 --> 00:06:25,540
things like the Pulse Polio
drops on the ground, that what

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00:06:25,540 --> 00:06:29,970
do we know whether it's
something like sterilization?

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So that's one example.

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Another very famous example is
the one child policy in China.

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So the one child policy
started in 1978, 1979.

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Very brutally because before
that Mao was actually in favor

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00:06:46,640 --> 00:06:50,130
of Chinese people having many
children because that would

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00:06:50,130 --> 00:06:54,650
constitute a large army of
people to construct the

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00:06:54,650 --> 00:06:57,200
country and to be strong
and all that.

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But then they realized that, oh,
we have too many people or

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00:06:59,865 --> 00:07:02,730
they believed we have too many
people and started the one

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00:07:02,730 --> 00:07:03,890
child policy.

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The one-child policy, at the
beginning, was very strict.

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00:07:06,550 --> 00:07:08,210
So basically you can only
have one child.

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The second child, not only the
parents get heavily fined, but

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00:07:12,170 --> 00:07:16,280
in addition the second child
has no rights, can't go to

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school, can't get health care,
can't get housing, can't get a

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permit to live somewhere.

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00:07:22,920 --> 00:07:25,400
So basically you don't want
to be a second child.

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So it was very effective
in terms have not

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having a second child.

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But they had one consequence,
which you probably have heard

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00:07:35,190 --> 00:07:38,960
of, which is the ratio of boys
to girls in China is

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00:07:38,960 --> 00:07:41,940
completely skewed in
the favor of boys.

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As of 1986, when Amartya Sen
wrote his famous paper on

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00:07:47,240 --> 00:07:51,690
missing women, it was 94 women
for 100 men in China.

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00:07:51,690 --> 00:07:55,470
And since then it's only gone
down and down, especially as

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00:07:55,470 --> 00:07:59,770
abortion became available and
in particular ultrasound

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00:07:59,770 --> 00:08:02,820
technology to figure out
the sex of the fetus.

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00:08:02,820 --> 00:08:07,830
So nowadays less infanticide
but more abortion.

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00:08:07,830 --> 00:08:09,940
So they've relaxed the policies
in a way that I'm

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00:08:09,940 --> 00:08:14,500
going to describe a little bit
later to allow in some places

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00:08:14,500 --> 00:08:16,770
people are to have a
second child if the

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00:08:16,770 --> 00:08:19,150
first child was a girl.

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So what is interesting about
that is it means that actually

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in those places the gender ratio
at first birth actually

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reverse where people were more
likely to keep a girl than to

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00:08:32,380 --> 00:08:35,429
keep a boy because that give
them a kind of second ticket

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00:08:35,429 --> 00:08:38,309
for the second child and they
could always abort the second

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00:08:38,309 --> 00:08:40,110
child if she was a girl.

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00:08:40,110 --> 00:08:44,500
So that's, again, another pretty
drastic policy which is

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00:08:44,500 --> 00:08:48,340
not popular at all and had
a lot of consequences.

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00:08:48,340 --> 00:08:51,360
So those are pretty extreme
examples, one of them.

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00:08:51,360 --> 00:08:54,210
But most of the poor people in
the world live in countries

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00:08:54,210 --> 00:09:00,300
where at some level or another
the government thinks that the

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00:09:00,300 --> 00:09:03,850
population is too big and
needs to be controlled.

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00:09:03,850 --> 00:09:08,670
And usually it's done in a more
civilized way of trying

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00:09:08,670 --> 00:09:11,600
to make contraceptives available
to people, convince

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00:09:11,600 --> 00:09:13,090
them to use them, et cetera.

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00:09:13,090 --> 00:09:16,320
And an example of an incentive
program of this kind is the

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00:09:16,320 --> 00:09:21,650
ICDDR, B in Bangladesh, which
was initially a big site where

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00:09:21,650 --> 00:09:26,790
they provided control of
diarrhea diseases--

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00:09:26,790 --> 00:09:30,300
so actually it's ICDDR,B because
diarrhea diseases,

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00:09:30,300 --> 00:09:34,320
Institute for the Control
of Diarrhea Diseases--

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00:09:34,320 --> 00:09:37,310
in one region called Matlab
in Bangladesh.

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00:09:37,310 --> 00:09:39,520
And then at some point they
started in about half the

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00:09:39,520 --> 00:09:43,000
villages in the region to
provide a lot of counseling.

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00:09:43,000 --> 00:09:48,650
There was a woman who was coming
to every house once a

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00:09:48,650 --> 00:09:51,870
week or twice a month to provide
advice and deliver

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00:09:51,870 --> 00:09:54,920
contraceptives and deliver
injectable contraceptives, et

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00:09:54,920 --> 00:09:57,230
cetera, to both make
contraception available and

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00:09:57,230 --> 00:09:59,350
try to change people's view.

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00:09:59,350 --> 00:10:04,150
So this one is a more usual form
of what intensive, or a

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00:10:04,150 --> 00:10:06,310
more benign form of what
intensive family planning

178
00:10:06,310 --> 00:10:07,560
policy can do.

179
00:10:09,820 --> 00:10:16,340
So why is policy so worried
about the number of children?

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00:10:16,340 --> 00:10:18,950
It really comes from this very
basic idea that if you have a

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00:10:18,950 --> 00:10:21,780
pie and you have more people
who want to share the pie,

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00:10:21,780 --> 00:10:24,970
there's going to be less
pie for every person.

183
00:10:24,970 --> 00:10:27,570
And if you really have too many
people around the pie,

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00:10:27,570 --> 00:10:30,820
you're going to have very small
slices for each person.

185
00:10:30,820 --> 00:10:33,920
So it's a pretty basic idea.

186
00:10:33,920 --> 00:10:37,900
This was, maybe not first, but
at least famously expressed by

187
00:10:37,900 --> 00:10:43,720
Malthus, who basically explained
that there are fixed

188
00:10:43,720 --> 00:10:44,590
factors in the world.

189
00:10:44,590 --> 00:10:47,430
For example, there is
only so much land.

190
00:10:47,430 --> 00:10:50,040
So because there is only so
much land, we can only

191
00:10:50,040 --> 00:10:52,480
grow so much food.

192
00:10:52,480 --> 00:10:54,810
So if we have large population,
we are fighting

193
00:10:54,810 --> 00:10:56,000
for this restricted food.

194
00:10:56,000 --> 00:10:57,950
Eventually we will starve.

195
00:10:57,950 --> 00:11:00,570
Now, the advantage is that this
is a stabilizing force

196
00:11:00,570 --> 00:11:03,160
because when everybody starves,
everybody dies.

197
00:11:03,160 --> 00:11:05,580
And when everybody dies, there
is again fewer people.

198
00:11:05,580 --> 00:11:08,870
So the remaining people
can again eat

199
00:11:08,870 --> 00:11:10,690
whatever food is left.

200
00:11:10,690 --> 00:11:15,380
And he cited as an example the
black death, which was a

201
00:11:15,380 --> 00:11:17,540
plague epidemic.

202
00:11:17,540 --> 00:11:25,330
So here's a poor person who
is affected by the plague.

203
00:11:25,330 --> 00:11:28,380
It was a huge epidemic
in Europe.

204
00:11:28,380 --> 00:11:32,520
If you have not seen The Seventh
Seal by Bergman, you

205
00:11:32,520 --> 00:11:34,360
should see it.

206
00:11:34,360 --> 00:11:39,320
It's about the plague in the
North and in Sweden.

207
00:11:39,320 --> 00:11:43,350
It was believed to have killed
half of the British population

208
00:11:43,350 --> 00:11:46,930
between 1348 and 1377.

209
00:11:46,930 --> 00:11:49,460
And Malthus explained
that this happened.

210
00:11:49,460 --> 00:11:50,570
Half the people died.

211
00:11:50,570 --> 00:11:54,950
And in the following century
wages kept rising.

212
00:11:54,950 --> 00:11:59,760
So that was, for him, an example
of what was going on.

213
00:11:59,760 --> 00:12:05,050
In the book we discussed the
more recent incarnation of

214
00:12:05,050 --> 00:12:08,480
Malthus' view and in particular
some analogous of

215
00:12:08,480 --> 00:12:10,090
the black death.

216
00:12:10,090 --> 00:12:13,125
What is it?

217
00:12:13,125 --> 00:12:14,079
Suzanna.

218
00:12:14,079 --> 00:12:15,510
AUDIENCE: HIV and AIDS.

219
00:12:15,510 --> 00:12:16,464
PROFESSOR: HIV and AIDS.

220
00:12:16,464 --> 00:12:20,910
So there is this professor at
the LSE, interestingly,

221
00:12:20,910 --> 00:12:21,510
[? Avignon ?]

222
00:12:21,510 --> 00:12:25,300
was also in England, who makes
the same argument saying HIV

223
00:12:25,300 --> 00:12:27,700
and AIDS, of course, it's
bad because people die.

224
00:12:27,700 --> 00:12:30,470
But people dying, in the end,
will free up productive

225
00:12:30,470 --> 00:12:33,790
resources both because
people are dying so

226
00:12:33,790 --> 00:12:34,680
that's fewer people.

227
00:12:34,680 --> 00:12:36,910
That's not great because the
people who are dying of HIV,

228
00:12:36,910 --> 00:12:40,310
AIDS are mostly the
active generation.

229
00:12:40,310 --> 00:12:43,010
So it's not great to
lose those guys.

230
00:12:43,010 --> 00:12:46,240
But the remaining people also
have fewer children.

231
00:12:46,240 --> 00:12:50,460
That should be good for
GDP per capita.

232
00:12:50,460 --> 00:12:55,100
That's a bit galling
as an idea.

233
00:12:55,100 --> 00:12:58,380
And the question is whether
it's true or not.

234
00:12:58,380 --> 00:13:03,240
So what is potentially wrong
in Malthus' argument about

235
00:13:03,240 --> 00:13:06,550
this idea that we have a fixed
pie, there is only so much

236
00:13:06,550 --> 00:13:09,735
land, we can only produce so
much food, and if we have more

237
00:13:09,735 --> 00:13:13,420
people, there'll be less
food for everyone?

238
00:13:13,420 --> 00:13:15,740
What's problematic
with this idea?

239
00:13:19,676 --> 00:13:21,644
AUDIENCE: He doesn't leave
room for innovation.

240
00:13:21,644 --> 00:13:24,596
So in the green revolution,
population pressures actually

241
00:13:24,596 --> 00:13:28,040
spurred technological innovation
that boosted green

242
00:13:28,040 --> 00:13:29,040
production.

243
00:13:29,040 --> 00:13:29,510
PROFESSOR: Exactly.

244
00:13:29,510 --> 00:13:32,100
It doesn't leave room
for innovation.

245
00:13:32,100 --> 00:13:37,100
So the first thing is when we
write down a production

246
00:13:37,100 --> 00:13:40,060
function, we tend to write down
the production function

247
00:13:40,060 --> 00:13:43,965
with a big A that multiplies how
much capital there is in

248
00:13:43,965 --> 00:13:46,670
the economy, which multiplies
how much labor

249
00:13:46,670 --> 00:13:48,300
there is in the economy.

250
00:13:48,300 --> 00:13:50,250
So that's how production
functions.

251
00:13:50,250 --> 00:13:54,370
The big A is these unknown
things that we discussed last

252
00:13:54,370 --> 00:13:56,610
time when we talked
about education.

253
00:13:56,610 --> 00:13:59,960
It's like the productivity,
the innovation,

254
00:13:59,960 --> 00:14:01,310
et cetera, of people.

255
00:14:01,310 --> 00:14:07,900
Usually we consider this A to be
non rival, which means that

256
00:14:07,900 --> 00:14:14,090
if you come up with a great
idea, your great idea can be

257
00:14:14,090 --> 00:14:17,190
used not only by you but
by anybody else.

258
00:14:17,190 --> 00:14:19,540
So, for example, if I come up
with a new thing in the Green

259
00:14:19,540 --> 00:14:22,740
Revolution then everyone
can use it.

260
00:14:22,740 --> 00:14:27,410
So the mechanically, if there
are more people around and if

261
00:14:27,410 --> 00:14:30,326
ideas tend to come in this kind
of random way, you know,

262
00:14:30,326 --> 00:14:32,320
every morning during your
shower you have some

263
00:14:32,320 --> 00:14:35,450
probability to come up with
the new seed for the Green

264
00:14:35,450 --> 00:14:38,650
Revolution or to come up with
the concept of iPad or to come

265
00:14:38,650 --> 00:14:44,060
up with a Facebook, then the
more people we are, the more

266
00:14:44,060 --> 00:14:48,010
chances there is that one of
us comes back with an idea.

267
00:14:48,010 --> 00:14:51,070
So this is a feature of all of
those models of technological

268
00:14:51,070 --> 00:14:57,680
progress, that the more people
we have, the more likely we

269
00:14:57,680 --> 00:15:00,960
are we have a good idea that's
going to benefit everyone.

270
00:15:00,960 --> 00:15:02,520
That's a feature of
models that people

271
00:15:02,520 --> 00:15:03,690
generally don't like.

272
00:15:03,690 --> 00:15:05,640
They think it's a bit strange.

273
00:15:05,640 --> 00:15:07,220
But why not?

274
00:15:07,220 --> 00:15:09,860
At the end of the
day that's true.

275
00:15:09,860 --> 00:15:12,360
And then there is the argument
that reinforces this effect

276
00:15:12,360 --> 00:15:14,970
furthermore, which is the
argument you had which is in

277
00:15:14,970 --> 00:15:19,090
addition, if we are about to
starve because there is so

278
00:15:19,090 --> 00:15:23,250
much population pressure then
that puts pressure on us to

279
00:15:23,250 --> 00:15:24,820
have more ideas.

280
00:15:24,820 --> 00:15:26,950
So that gives us all the
right incentive to try

281
00:15:26,950 --> 00:15:28,530
and figure it out.

282
00:15:28,530 --> 00:15:31,280
For these two reasons, what we
should expect is when there

283
00:15:31,280 --> 00:15:35,020
are more people around, people
have more ideas, and therefore

284
00:15:35,020 --> 00:15:37,800
growth is also faster.

285
00:15:37,800 --> 00:15:41,720
So there is a very interesting
paper by Micheal Kramer which

286
00:15:41,720 --> 00:15:49,340
looks at that in the world.

287
00:15:49,340 --> 00:15:54,470
So this is population growth
five million BC to 1990.

288
00:15:54,470 --> 00:15:56,920
As you can imagine, the quality
of the data improved a

289
00:15:56,920 --> 00:15:59,960
little bit between 5 million
BC and 1990.

290
00:15:59,960 --> 00:16:02,910
And the data points in
five million BC are

291
00:16:02,910 --> 00:16:06,150
a little bit scanty.

292
00:16:06,150 --> 00:16:17,880
However, what he does here is
that he has periods of data.

293
00:16:17,880 --> 00:16:21,030
So his first point is from
five million BC.

294
00:16:21,030 --> 00:16:22,290
It's estimated, obviously.

295
00:16:22,290 --> 00:16:24,760
Then the second might
be one million BC.

296
00:16:24,760 --> 00:16:27,180
So that's a very long
period of time.

297
00:16:27,180 --> 00:16:32,405
And then he may have annual data
between 1960 and 1990.

298
00:16:32,405 --> 00:16:35,210
But what he does is for each
period he has, he calculates

299
00:16:35,210 --> 00:16:39,610
the annual growth rate of
population in between one year

300
00:16:39,610 --> 00:16:43,240
and the next year and regresses
here or plots it

301
00:16:43,240 --> 00:16:46,010
against how much population
there was at the time.

302
00:16:46,010 --> 00:16:47,670
This is done world wide.

303
00:16:47,670 --> 00:16:51,790
So this is population growth
rate on population billion.

304
00:16:51,790 --> 00:16:54,770
And what we see is the exact
opposite as the Malthusian

305
00:16:54,770 --> 00:16:58,260
graph, which is particularly the
more people there are, the

306
00:16:58,260 --> 00:17:00,190
faster the population growth.

307
00:17:00,190 --> 00:17:02,180
And that's about linear.

308
00:17:02,180 --> 00:17:05,940
So the more people we are, the
more our population grows,

309
00:17:05,940 --> 00:17:09,720
which suggests that this idea
for fixed land is wrong

310
00:17:09,720 --> 00:17:11,470
because that would go the other
way, that there's no

311
00:17:11,470 --> 00:17:15,680
stabilizing force that brings
the population back to zero,

312
00:17:15,680 --> 00:17:19,460
and instead it's the opposite
that happens.

313
00:17:19,460 --> 00:17:24,339
So far, there has not been
really any evidence that the

314
00:17:24,339 --> 00:17:26,319
Malthusian theory was right.

315
00:17:26,319 --> 00:17:29,250
In fact, we have many, many more
people than we were in

316
00:17:29,250 --> 00:17:30,620
Malthus' time.

317
00:17:30,620 --> 00:17:34,550
And people are by and large much
richer than they were in

318
00:17:34,550 --> 00:17:38,310
Malthus' time and eating much
more and healthier and having

319
00:17:38,310 --> 00:17:39,420
longer lives.

320
00:17:39,420 --> 00:17:41,920
So it doesn't seem that if you
look at the very short history

321
00:17:41,920 --> 00:17:51,420
of the world you get so scared
by what's going on here.

322
00:17:51,420 --> 00:17:55,890
And yet these Malthusian
arguments in a form or another

323
00:17:55,890 --> 00:17:58,240
somehow never dies.

324
00:17:58,240 --> 00:18:00,430
It always keeps coming back.

325
00:18:00,430 --> 00:18:03,950
And interestingly where it
mostly recently came back or

326
00:18:03,950 --> 00:18:08,675
more permanently came back is in
Jeff Sachs' new book-- not

327
00:18:08,675 --> 00:18:11,280
the End of Poverty book that
we discussed before.

328
00:18:11,280 --> 00:18:13,290
But he has a book called
Common Wealth.

329
00:18:13,290 --> 00:18:17,100
And the subtitle is Economics
for a Crowded Planet.

330
00:18:17,100 --> 00:18:19,370
So that pretty much
said it all.

331
00:18:19,370 --> 00:18:22,270
The planet is crowded,
too crowded.

332
00:18:22,270 --> 00:18:25,100
One of the main challenges
is population.

333
00:18:25,100 --> 00:18:28,400
This, I took from his website
where he kind of

334
00:18:28,400 --> 00:18:29,550
advertises the book.

335
00:18:29,550 --> 00:18:31,970
"Stabilizing the world's
population is crucial to

336
00:18:31,970 --> 00:18:34,100
ensuring peace and prosperity
on this

337
00:18:34,100 --> 00:18:35,800
already crowded planet.

338
00:18:35,800 --> 00:18:38,590
If we ignore this issue, we risk
a massive and unsettling

339
00:18:38,590 --> 00:18:42,260
youth bulge, unbearable
environmental pressures, and

340
00:18:42,260 --> 00:18:44,280
unchecked global migration."

341
00:18:44,280 --> 00:18:47,280
So the "unbearable environmental
pressure," that

342
00:18:47,280 --> 00:18:51,820
refers to exactly the type of
limited resource argument that

343
00:18:51,820 --> 00:18:57,780
we can have in the
Malthusian world.

344
00:18:57,780 --> 00:18:59,720
So what are the environmental
pressure that

345
00:18:59,720 --> 00:19:00,970
he's worried about?

346
00:19:07,065 --> 00:19:09,005
AUDIENCE: The more people you
have, the more green house

347
00:19:09,005 --> 00:19:10,600
gasses we emit.

348
00:19:10,600 --> 00:19:10,710
PROFESSOR: Sorry.

349
00:19:10,710 --> 00:19:12,614
Say it again.

350
00:19:12,614 --> 00:19:14,566
AUDIENCE: The more people you
have, the more green house

351
00:19:14,566 --> 00:19:15,550
gasses you can emit.

352
00:19:15,550 --> 00:19:15,620
PROFESSOR: Right.

353
00:19:15,620 --> 00:19:20,250
So climate is one, that maybe
more people generate more

354
00:19:20,250 --> 00:19:23,966
greenhouse emission.

355
00:19:23,966 --> 00:19:25,962
AUDIENCE: Water because we
have a fixed amount of

356
00:19:25,962 --> 00:19:27,459
freshwater that we can access.

357
00:19:27,459 --> 00:19:30,453
But the more people there are,
we have to grow more food.

358
00:19:30,453 --> 00:19:31,451
We have to irrigate
all of that.

359
00:19:31,451 --> 00:19:33,946
And it's important that we
have access to clean

360
00:19:33,946 --> 00:19:36,940
water for daily use.

361
00:19:36,940 --> 00:19:37,440
PROFESSOR: Right.

362
00:19:37,440 --> 00:19:38,660
Water is one.

363
00:19:38,660 --> 00:19:40,810
There is big pressure
on fresh water.

364
00:19:45,750 --> 00:19:46,900
And what's the last?

365
00:19:46,900 --> 00:19:47,684
Yeah.

366
00:19:47,684 --> 00:19:48,910
AUDIENCE: Energy.

367
00:19:48,910 --> 00:19:49,260
PROFESSOR: Energy.

368
00:19:49,260 --> 00:19:52,080
And particularly there
is only so much oil.

369
00:19:52,080 --> 00:19:56,500
So until we figure out
something else--

370
00:19:56,500 --> 00:19:59,860
and certainly nuclear energy
is probably going

371
00:19:59,860 --> 00:20:01,110
to be one of them--

372
00:20:03,670 --> 00:20:05,460
there is also going
to be eventually a

373
00:20:05,460 --> 00:20:07,480
pressure for that.

374
00:20:07,480 --> 00:20:10,890
And what's the last one that
we discussed in one of the

375
00:20:10,890 --> 00:20:12,480
first lectures that
people also have

376
00:20:12,480 --> 00:20:13,730
brought up this year?

377
00:20:22,640 --> 00:20:23,610
AUDIENCE: Food.

378
00:20:23,610 --> 00:20:23,870
PROFESSOR: Food.

379
00:20:23,870 --> 00:20:24,550
Exactly.

380
00:20:24,550 --> 00:20:28,150
In the end, food is back.

381
00:20:28,150 --> 00:20:29,730
Can I ask you guys to not
do something else?

382
00:20:29,730 --> 00:20:30,640
It's a bit unsettling.

383
00:20:30,640 --> 00:20:33,360
There are too many people who
are doing something else.

384
00:20:33,360 --> 00:20:35,730
I am pretty tolerant
with that.

385
00:20:35,730 --> 00:20:36,730
But that's just too much.

386
00:20:36,730 --> 00:20:41,430
Like, there's half the class
with computers open.

387
00:20:41,430 --> 00:20:45,590
I'm assuming that about 90% of
you are checking some other

388
00:20:45,590 --> 00:20:46,840
website or whatever.

389
00:20:49,450 --> 00:20:51,230
That doesn't help my focus.

390
00:20:51,230 --> 00:20:55,720
So if you are doing something
else, just shut your computer.

391
00:20:55,720 --> 00:20:56,970
Thanks.

392
00:21:01,250 --> 00:21:07,080
And so is there reason
to worry about that?

393
00:21:10,040 --> 00:21:13,560
Indeed, what we do find that is
something pretty striking

394
00:21:13,560 --> 00:21:18,050
is that the countries that have
higher fertility rate are

395
00:21:18,050 --> 00:21:19,530
much poorer.

396
00:21:19,530 --> 00:21:21,210
So here it's plotted in
the other direction.

397
00:21:21,210 --> 00:21:23,790
We have the wealth of
the country and

398
00:21:23,790 --> 00:21:25,160
the fertility rate.

399
00:21:25,160 --> 00:21:26,730
It's a nice log relationship.

400
00:21:26,730 --> 00:21:29,260
If we were plotting it in log,
that would be log linear.

401
00:21:29,260 --> 00:21:30,272
Yep.

402
00:21:30,272 --> 00:21:32,045
AUDIENCE: Is there any
investigation about why Saudi

403
00:21:32,045 --> 00:21:34,298
Arabia and Israel are
so noticeably

404
00:21:34,298 --> 00:21:37,770
removed from the trend?

405
00:21:37,770 --> 00:21:38,740
PROFESSOR: So what
do you think?

406
00:21:38,740 --> 00:21:43,020
So the first thing,
why are they both

407
00:21:43,020 --> 00:21:45,040
removed from the trend?

408
00:21:45,040 --> 00:21:46,590
AUDIENCE: They have higher
fertility rates than you'd

409
00:21:46,590 --> 00:21:48,900
expect for their GDP.

410
00:21:48,900 --> 00:21:49,200
PROFESSOR: Exactly.

411
00:21:49,200 --> 00:21:52,550
They are richer than you'd
expect given how

412
00:21:52,550 --> 00:21:53,770
populous they are.

413
00:21:53,770 --> 00:21:55,933
So how about Saudi Arabia?

414
00:21:55,933 --> 00:21:58,200
AUDIENCE: Oil.

415
00:21:58,200 --> 00:22:00,100
PROFESSOR: They have oil,
so they are pretty rich.

416
00:22:00,100 --> 00:22:00,710
Israel?

417
00:22:00,710 --> 00:22:01,660
AUDIENCE: They have
an existential

418
00:22:01,660 --> 00:22:02,610
threat to their existence.

419
00:22:02,610 --> 00:22:04,510
They want to populate more?

420
00:22:04,510 --> 00:22:07,400
PROFESSOR: Yeah.

421
00:22:07,400 --> 00:22:08,860
That's a very good
way to set it.

422
00:22:08,860 --> 00:22:11,090
They have an existential threat
to their existence.

423
00:22:11,090 --> 00:22:13,680
On the other hand, it's an

424
00:22:13,680 --> 00:22:15,460
intellectually very rich country.

425
00:22:15,460 --> 00:22:17,590
They also get a lot
of support.

426
00:22:17,590 --> 00:22:21,280
And it's also very small,
so that might

427
00:22:21,280 --> 00:22:22,470
eventually create issues.

428
00:22:22,470 --> 00:22:25,310
In fact, that does
create issues.

429
00:22:25,310 --> 00:22:29,040
But that's probably the reason
why Israel is so much richer

430
00:22:29,040 --> 00:22:30,800
compared to their income.

431
00:22:30,800 --> 00:22:35,850
And the Israel case kind of
illustrates well the problem

432
00:22:35,850 --> 00:22:39,070
with this graph which is you
could read from this graph

433
00:22:39,070 --> 00:22:44,060
that, oh, having a large
population makes you poor.

434
00:22:44,060 --> 00:22:47,210
Or you could read from this
graph that poor countries have

435
00:22:47,210 --> 00:22:50,540
more kids or richer countries
have fewer kids in the

436
00:22:50,540 --> 00:22:51,180
opposite direction.

437
00:22:51,180 --> 00:22:53,470
That is, the lack of wealth that
makes people have a lot

438
00:22:53,470 --> 00:22:57,930
of children maybe because
of people's choices.

439
00:22:57,930 --> 00:23:00,840
Because when we explain Isreal,
we don't want to

440
00:23:00,840 --> 00:23:03,640
explain why Israel is rich
despite having many children.

441
00:23:03,640 --> 00:23:07,820
We want to explain why Israel
has high fertility rate

442
00:23:07,820 --> 00:23:09,600
despite being rich.

443
00:23:09,600 --> 00:23:13,600
So we explain here what are
the reasons why people in

444
00:23:13,600 --> 00:23:14,940
Israel would like kids.

445
00:23:14,940 --> 00:23:16,190
That's not the case in
other countries.

446
00:23:19,680 --> 00:23:21,470
So that's kind of what
I'm saying here.

447
00:23:21,470 --> 00:23:24,290
As usual, the correlation
could go either way.

448
00:23:24,290 --> 00:23:26,910
We could find that poor
countries could be poor

449
00:23:26,910 --> 00:23:29,055
because they are too crowded.

450
00:23:29,055 --> 00:23:31,010
A rich country could have
lower fertility

451
00:23:31,010 --> 00:23:33,140
because they are rich.

452
00:23:33,140 --> 00:23:37,320
Maybe as people become richer,
the opportunity cost of their

453
00:23:37,320 --> 00:23:39,350
time is higher.

454
00:23:39,350 --> 00:23:44,170
As a country becomes richer,
women are more likely to find

455
00:23:44,170 --> 00:23:46,850
things that they can do
in the labor market.

456
00:23:46,850 --> 00:23:49,560
And therefore women are more
likely to participate in the

457
00:23:49,560 --> 00:23:51,140
labor market.

458
00:23:51,140 --> 00:23:54,170
And therefore, having a kid, you
know, you don't want to be

459
00:23:54,170 --> 00:23:57,370
taking off a year of your life
every other year because you

460
00:23:57,370 --> 00:24:00,780
are bearing or nursing
a very small child.

461
00:24:00,780 --> 00:24:02,930
So it's kind of difficult
to answer this question.

462
00:24:02,930 --> 00:24:07,630
It's not going to be solvable by
looking at other countries.

463
00:24:07,630 --> 00:24:10,600
And it's even harder to ask what
population increase would

464
00:24:10,600 --> 00:24:12,900
do to the planet.

465
00:24:12,900 --> 00:24:15,410
It might be right even
if Malthus was wrong.

466
00:24:15,410 --> 00:24:17,040
The [INAUDIBLE] might
still be right.

467
00:24:17,040 --> 00:24:21,520
It might be right that we will
never find a solution to get

468
00:24:21,520 --> 00:24:24,130
clean water access to everyone,
especially if it's a

469
00:24:24,130 --> 00:24:28,050
much larger group of people.

470
00:24:28,050 --> 00:24:29,000
It might also be wrong.

471
00:24:29,000 --> 00:24:30,970
But it's difficult to know.

472
00:24:30,970 --> 00:24:31,910
Yep.

473
00:24:31,910 --> 00:24:33,320
AUDIENCE: Is there a correlation
with religion in

474
00:24:33,320 --> 00:24:36,150
fertility at all?

475
00:24:36,150 --> 00:24:37,270
PROFESSOR: I would assume so.

476
00:24:37,270 --> 00:24:39,560
I don't know which
way it is though.

477
00:24:39,560 --> 00:24:41,090
It used to be that Catholic
country would

478
00:24:41,090 --> 00:24:43,030
have a lot of children.

479
00:24:43,030 --> 00:24:45,040
And now it's not true anymore.

480
00:24:45,040 --> 00:24:47,510
The countries that have the
fewer children in Europe are

481
00:24:47,510 --> 00:24:48,910
the traditionally Catholic
countries

482
00:24:48,910 --> 00:24:51,440
like Italy and Spain.

483
00:24:51,440 --> 00:24:53,860
So actually I think there is a
correlation, and I don't even

484
00:24:53,860 --> 00:24:54,710
know what it is.

485
00:24:54,710 --> 00:24:57,900
Like, for example,
what are the--

486
00:24:57,900 --> 00:25:00,600
but you're right.

487
00:25:00,600 --> 00:25:03,810
That brings to the number of
children you decide to have,

488
00:25:03,810 --> 00:25:06,043
et cetera, depends on
your culture as

489
00:25:06,043 --> 00:25:08,920
well as other things.

490
00:25:08,920 --> 00:25:12,090
So it's difficult to say
anything about countries.

491
00:25:12,090 --> 00:25:14,700
It's even harder to say anything
about the world.

492
00:25:14,700 --> 00:25:18,190
So we can go back to our
traditional refuge and start

493
00:25:18,190 --> 00:25:22,200
looking at the family and ask
whether it is true that a

494
00:25:22,200 --> 00:25:24,930
small family is a
happy family.

495
00:25:24,930 --> 00:25:28,845
And, of course, that's not
necessarily the answer of what

496
00:25:28,845 --> 00:25:31,530
it would be for a country or
let alone for the world

497
00:25:31,530 --> 00:25:34,620
because there are externalities
of a large

498
00:25:34,620 --> 00:25:38,060
population in a country or in
a community or in the world

499
00:25:38,060 --> 00:25:39,370
that the family might
not internalize

500
00:25:39,370 --> 00:25:41,210
or take into account.

501
00:25:41,210 --> 00:25:46,045
For example, having more kids,
the kids may still be as

502
00:25:46,045 --> 00:25:49,230
educated and you may have
as much water to

503
00:25:49,230 --> 00:25:51,090
feed the kids today.

504
00:25:51,090 --> 00:25:53,760
But the fact that you have just
one more kid puts more

505
00:25:53,760 --> 00:25:58,990
pressure on water resources
for everyone in the world.

506
00:25:58,990 --> 00:26:03,670
So we are not fully answering
the question were we answering

507
00:26:03,670 --> 00:26:07,600
this particular question on
what happened to family.

508
00:26:07,600 --> 00:26:12,090
However, it's still an important
question because, in

509
00:26:12,090 --> 00:26:17,490
fact, even if you where
convinced that family or that

510
00:26:17,490 --> 00:26:20,680
large population is a problem
for the world as a whole and

511
00:26:20,680 --> 00:26:23,980
you really want to deal with
it, even if you were that

512
00:26:23,980 --> 00:26:26,670
convinced you would have
to find a way to do it.

513
00:26:26,670 --> 00:26:31,480
And the issue is an effective
way to do it would certainly

514
00:26:31,480 --> 00:26:34,670
depend on whether having a
large family is something

515
00:26:34,670 --> 00:26:36,100
that's immediate costly
to people.

516
00:26:36,100 --> 00:26:38,490
And therefore you need to make
them realize that, and then

517
00:26:38,490 --> 00:26:40,950
they'll have fewer children on
their own or whether it's

518
00:26:40,950 --> 00:26:43,110
something that's beneficial
to people.

519
00:26:43,110 --> 00:26:45,590
So we need to answer this
question even if we are

520
00:26:45,590 --> 00:26:50,030
interested just in the external
world wide effect of

521
00:26:50,030 --> 00:26:51,710
large population.

522
00:26:51,710 --> 00:26:54,910
Moreover, if you find out, for
example, that it's very bad

523
00:26:54,910 --> 00:26:58,640
for children to live in a large
family then you could

524
00:26:58,640 --> 00:27:02,950
want to design a population
family that would increase the

525
00:27:02,950 --> 00:27:10,060
cost of having children by ideas
ranging from I'm going

526
00:27:10,060 --> 00:27:13,510
to reduce the cost of not having
them by reducing the

527
00:27:13,510 --> 00:27:16,290
cost of contraception to I'm
going to make it illegal to

528
00:27:16,290 --> 00:27:18,350
have more than one
child in China.

529
00:27:18,350 --> 00:27:22,920
So if we consider that parents
are not fully maximizing the

530
00:27:22,920 --> 00:27:26,890
welfare of their children and of
the second generation then

531
00:27:26,890 --> 00:27:33,600
we might be even more concerned
about a population

532
00:27:33,600 --> 00:27:36,460
policy for the sake of the
children, even if we weren't

533
00:27:36,460 --> 00:27:38,790
sure of what it would do to the
world as a whole to have

534
00:27:38,790 --> 00:27:40,540
fewer or more kids.

535
00:27:40,540 --> 00:27:43,260
So these reasons, that's a
question which is pretty much

536
00:27:43,260 --> 00:27:44,430
immediately important.

537
00:27:44,430 --> 00:27:47,680
And if you read Sachs' book,
Common Wealth, he's going to

538
00:27:47,680 --> 00:27:50,500
tell you very assertively,
very authoritatively.

539
00:27:50,500 --> 00:27:53,480
He's going to tell you that
large families are bad for

540
00:27:53,480 --> 00:27:56,770
kids, that there is plenty of
evidence that large families

541
00:27:56,770 --> 00:27:58,200
are bad for kids.

542
00:27:58,200 --> 00:28:03,790
And that's not really
the subject I study.

543
00:28:03,790 --> 00:28:07,750
So when I went into this to
review the evidence when we

544
00:28:07,750 --> 00:28:11,775
were preparing the book, I
assumed that I would find a

545
00:28:11,775 --> 00:28:15,630
number of studies finding
exactly this.

546
00:28:15,630 --> 00:28:20,180
And, of course, when you look at
the reason we assume that,

547
00:28:20,180 --> 00:28:23,750
well, that seems, again, pretty
much intuitive that if

548
00:28:23,750 --> 00:28:27,630
you have a larger family, that's
more people on one

549
00:28:27,630 --> 00:28:28,610
single pie.

550
00:28:28,610 --> 00:28:30,370
That's fewer to eat
for everyone.

551
00:28:30,370 --> 00:28:34,080
There's also a very, very famous
paper by Gary Becker

552
00:28:34,080 --> 00:28:37,070
who won the Nobel Prize for his
work on the economics of

553
00:28:37,070 --> 00:28:40,740
the family, which coined
the term the quality

554
00:28:40,740 --> 00:28:42,170
quantity trade off.

555
00:28:42,170 --> 00:28:45,090
And the quality quantity trade
off is exactly that.

556
00:28:45,090 --> 00:28:49,460
Siblings compete for resources,
parental attention,

557
00:28:49,460 --> 00:28:51,280
money, time, et cetera.

558
00:28:51,280 --> 00:28:54,030
So if you have more siblings,
they will compete for this.

559
00:28:54,030 --> 00:28:56,610
And, therefore, it's bad
for all of them.

560
00:28:56,610 --> 00:29:00,720
So the paper starts from this as
an assumption and then from

561
00:29:00,720 --> 00:29:03,620
this assumption builds a model
which shows that suppose that

562
00:29:03,620 --> 00:29:05,500
the quality is a normal good.

563
00:29:05,500 --> 00:29:07,030
So you want more quality
children

564
00:29:07,030 --> 00:29:08,730
when you become richer.

565
00:29:08,730 --> 00:29:11,920
Then as people become richer,
they will move on the quality

566
00:29:11,920 --> 00:29:16,340
quantity trade off towards fewer
kids of higher quality.

567
00:29:16,340 --> 00:29:19,280
So the paper's argument
was not--

568
00:29:19,280 --> 00:29:22,380
the first one with the second
one which is given the quality

569
00:29:22,380 --> 00:29:25,050
quantity trade off, we should
see that richer family have

570
00:29:25,050 --> 00:29:26,930
fewer children of
higher quality.

571
00:29:26,930 --> 00:29:30,215
So I sort of assumed that it was
a given that this quality

572
00:29:30,215 --> 00:29:31,650
quantity trade off existed.

573
00:29:35,710 --> 00:29:39,460
Now, another thing that if you
look at the data you do find,

574
00:29:39,460 --> 00:29:45,020
as [? West ?] pointed out
earlier, that in general it's

575
00:29:45,020 --> 00:29:47,870
true that children are of lower

576
00:29:47,870 --> 00:29:49,880
quality in larger families.

577
00:29:49,880 --> 00:29:56,115
They tend to have less
education, to be smaller, et

578
00:29:56,115 --> 00:29:57,470
cetera, when they have
more siblings.

579
00:29:57,470 --> 00:29:59,020
It's not even always true.

580
00:29:59,020 --> 00:30:01,620
But it tends to be true.

581
00:30:01,620 --> 00:30:04,720
The problem, of course, is we
can't look at that because

582
00:30:04,720 --> 00:30:08,710
even in Baker's model he just
explained to us that because

583
00:30:08,710 --> 00:30:11,720
there is this trade off between
quality and quantity,

584
00:30:11,720 --> 00:30:14,905
the families where we are going
to see many children are

585
00:30:14,905 --> 00:30:16,690
precisely the families
which don't care

586
00:30:16,690 --> 00:30:19,020
so much about quality.

587
00:30:19,020 --> 00:30:22,500
So even if we manage to force
them not too have many

588
00:30:22,500 --> 00:30:27,205
children, they would still want
lower quality children

589
00:30:27,205 --> 00:30:29,360
and would spend their money
on other things

590
00:30:29,360 --> 00:30:30,740
than quality children.

591
00:30:30,740 --> 00:30:37,420
That goes back to the first
concepts we saw when we looked

592
00:30:37,420 --> 00:30:40,820
at program evaluation and this
idea of potential outcome.

593
00:30:40,820 --> 00:30:45,510
The potential outcome, the
potential quality of the

594
00:30:45,510 --> 00:30:49,110
children born in large families,
is lower than the

595
00:30:49,110 --> 00:30:53,670
potential quality of the
children born in small

596
00:30:53,670 --> 00:30:58,320
families, keeping the family
size constant just because the

597
00:30:58,320 --> 00:31:01,910
people who have large families
in Baker and Tomms' world are

598
00:31:01,910 --> 00:31:04,060
people who care less about the
quality of the children.

599
00:31:04,060 --> 00:31:05,930
I don't know if that is right.

600
00:31:05,930 --> 00:31:07,840
But under this model that
we are trying to

601
00:31:07,840 --> 00:31:09,180
test I would be right.

602
00:31:09,180 --> 00:31:13,640
That means we cannot look
at just the correlation.

603
00:31:13,640 --> 00:31:16,870
More specifically, we
know that poorer

604
00:31:16,870 --> 00:31:17,660
families are larger.

605
00:31:17,660 --> 00:31:21,070
And therefore it is likely
that large family is

606
00:31:21,070 --> 00:31:23,270
correlated with poverty, which
would make children less

607
00:31:23,270 --> 00:31:25,690
educated for all sorts
of reasons.

608
00:31:25,690 --> 00:31:28,360
So what can we look at?

609
00:31:28,360 --> 00:31:33,200
We need to look at things that
somehow have forced families

610
00:31:33,200 --> 00:31:38,890
to be larger or smaller than
people wanted them to be.

611
00:31:38,890 --> 00:31:43,920
Or we need to look at policies
that made it easier or harder

612
00:31:43,920 --> 00:31:47,540
for people to control
their family.

613
00:31:47,540 --> 00:31:51,580
So what is a thing that makes
your family bigger than you

614
00:31:51,580 --> 00:31:54,012
may have planned it to be?

615
00:31:54,012 --> 00:31:55,860
AUDIENCE: Having twins was
one of these, I guess.

616
00:31:55,860 --> 00:31:58,182
PROFESSOR: Having twins, yes.

617
00:31:58,182 --> 00:32:00,146
And what is another one?

618
00:32:00,146 --> 00:32:03,583
AUDIENCE: In some families, in
some countries that consider

619
00:32:03,583 --> 00:32:05,056
that they really want
to have a boy.

620
00:32:05,056 --> 00:32:07,511
Let's say their first
child is a girl.

621
00:32:07,511 --> 00:32:10,702
They're more likely to have
more children because they

622
00:32:10,702 --> 00:32:11,950
want [INAUDIBLE].

623
00:32:11,950 --> 00:32:14,170
PROFESSOR: Exactly, the
gender of the family.

624
00:32:14,170 --> 00:32:20,250
So, specifically, before sex
selection was available,

625
00:32:20,250 --> 00:32:22,240
gender was more or
less exogenous.

626
00:32:22,240 --> 00:32:24,795
Or in places where people
don't do sex selective

627
00:32:24,795 --> 00:32:27,660
abortion, gender is more
or less exogenous.

628
00:32:27,660 --> 00:32:30,400
So if you really want a boy
and you have a girl then

629
00:32:30,400 --> 00:32:31,990
you're going to have
one more child.

630
00:32:31,990 --> 00:32:34,250
This means, by the way, that
girls tend to live in large

631
00:32:34,250 --> 00:32:37,690
families, which could be one
reason why girls do worse in

632
00:32:37,690 --> 00:32:40,820
life than boys, not because
people treat them worse once

633
00:32:40,820 --> 00:32:44,950
they are born but because they
live in large families.

634
00:32:44,950 --> 00:32:51,170
Now, another thing related to
the gender of the children is

635
00:32:51,170 --> 00:32:53,720
that in a lot of cases people
want to have a mix

636
00:32:53,720 --> 00:32:55,440
composition.

637
00:32:55,440 --> 00:32:58,710
So for example in the US, you
are more likely to have a

638
00:32:58,710 --> 00:33:02,680
third child if your first two
children were of the same

639
00:33:02,680 --> 00:33:05,380
gender, say, two boys
or two girls.

640
00:33:05,380 --> 00:33:08,955
You are about 8% more likely
to have a third one.

641
00:33:08,955 --> 00:33:11,287
And that, again, conditional
on the gender

642
00:33:11,287 --> 00:33:11,865
of the first child.

643
00:33:11,865 --> 00:33:16,740
The gender of the second one is
random in the US, assuming

644
00:33:16,740 --> 00:33:21,390
people don't abort kids
based on their gender.

645
00:33:21,390 --> 00:33:26,060
Then therefore we can use that
to look at the effect of a

646
00:33:26,060 --> 00:33:29,425
larger family size than you
would otherwise have had

647
00:33:29,425 --> 00:33:32,940
because now we have two families
that are all exactly

648
00:33:32,940 --> 00:33:35,640
the same, except one of them end
up with three kids and one

649
00:33:35,640 --> 00:33:37,750
of them ends up with two kids,
either because of a twin in

650
00:33:37,750 --> 00:33:42,005
the second birth or because
of this gender selection.

651
00:33:45,050 --> 00:33:48,130
So of course with the twins,
we cannot look at the twins

652
00:33:48,130 --> 00:33:50,620
themselves.

653
00:33:50,620 --> 00:33:53,620
Why looking at the twins
themselves would be

654
00:33:53,620 --> 00:33:54,870
problematic?

655
00:33:59,400 --> 00:34:01,820
AUDIENCE: Because at the point
when the twins arrive,

656
00:34:01,820 --> 00:34:04,520
there's, like, nothing to
compare it to, right?

657
00:34:04,520 --> 00:34:07,280
So wouldn't it be more useful
to look at situations where

658
00:34:07,280 --> 00:34:10,154
there was a single kid and then
the second child ended up

659
00:34:10,154 --> 00:34:11,330
being twins?

660
00:34:11,330 --> 00:34:11,840
PROFESSOR: Right.

661
00:34:11,840 --> 00:34:16,230
So you could say let me compare
at first births the

662
00:34:16,230 --> 00:34:17,980
families which have
twins versus

663
00:34:17,980 --> 00:34:18,830
families which have one.

664
00:34:18,830 --> 00:34:20,861
You would compare two to one.

665
00:34:20,861 --> 00:34:22,855
And why wouldn't we want
to do that comparison?

666
00:34:29,474 --> 00:34:31,429
AUDIENCE: Can you repeat
the question?

667
00:34:31,429 --> 00:34:34,820
PROFESSOR: So suppose that
I want to use twins.

668
00:34:34,820 --> 00:34:37,164
And I'm saying let me focus
on first birth.

669
00:34:37,164 --> 00:34:40,471
And I am going to compare all
of the kids that are born as

670
00:34:40,471 --> 00:34:44,280
single children and all of the
kids that are born as twins.

671
00:34:44,280 --> 00:34:48,929
So the twins are two, and the
singles children as one.

672
00:34:48,929 --> 00:34:50,260
Is this comparison valid?

673
00:34:50,260 --> 00:34:51,989
AUDIENCE: No.

674
00:34:51,989 --> 00:34:52,963
PROFESSOR: So why?

675
00:34:52,963 --> 00:34:56,544
AUDIENCE: Because isn't it the
case that we just talked about

676
00:34:56,544 --> 00:34:57,409
the fact that it's safe.

677
00:34:57,409 --> 00:35:00,373
If you get a kid, then
you want another kid.

678
00:35:00,373 --> 00:35:03,337
Then you can say if I get twins,
then I'll have one more

679
00:35:03,337 --> 00:35:05,313
than I actually intended to.

680
00:35:05,313 --> 00:35:11,510
But if you want a kid and
then you get twins--

681
00:35:11,510 --> 00:35:13,410
I don't know what the
expression is.

682
00:35:13,410 --> 00:35:15,810
PROFESSOR: You mean you are
saying that the kid who is

683
00:35:15,810 --> 00:35:18,230
single birth eventually
will have a brother.

684
00:35:18,230 --> 00:35:21,160
So maybe twins at first birth
might not change the total

685
00:35:21,160 --> 00:35:21,956
family size?

686
00:35:21,956 --> 00:35:22,650
AUDIENCE: Right.

687
00:35:22,650 --> 00:35:24,810
PROFESSOR: So that's true, which
is there might not be an

688
00:35:24,810 --> 00:35:28,400
effect on total family size or
the effect might be very small

689
00:35:28,400 --> 00:35:32,540
because almost everyone wants at
least two, in which case if

690
00:35:32,540 --> 00:35:34,570
we go with [? Deck's ?]

691
00:35:34,570 --> 00:35:37,870
idea of saying let's look at the
second birth and you move

692
00:35:37,870 --> 00:35:40,970
from two to three, and maybe
there are fewer kids who would

693
00:35:40,970 --> 00:35:43,660
want three, that creates a
bigger impact on family size.

694
00:35:43,660 --> 00:35:44,460
That's right.

695
00:35:44,460 --> 00:35:50,075
And there is another problem
with twins, pretty obvious,

696
00:35:50,075 --> 00:35:53,366
like, direct.

697
00:35:53,366 --> 00:35:55,466
You guys are over thinking it.

698
00:35:55,466 --> 00:35:55,952
Yeah.

699
00:35:55,952 --> 00:35:56,924
AUDIENCE: I don't know
if this is it.

700
00:35:56,924 --> 00:35:59,840
But the reason I think you
couldn't hurt the kids who

701
00:35:59,840 --> 00:36:01,784
weren't twins because if you're
a twin you'd probably

702
00:36:01,784 --> 00:36:03,242
get fewer nutrients.

703
00:36:03,242 --> 00:36:06,644
So you're less likely,
especially in countries with

704
00:36:06,644 --> 00:36:09,236
poor families, they're
less likely to

705
00:36:09,236 --> 00:36:10,060
have the same potential.

706
00:36:10,060 --> 00:36:10,650
PROFESSOR: Yeah, exactly.

707
00:36:10,650 --> 00:36:11,720
That's the problem.

708
00:36:11,720 --> 00:36:13,800
Twins are fragile.

709
00:36:13,800 --> 00:36:16,850
Even here they are born
with lower weight.

710
00:36:16,850 --> 00:36:22,300
They are more easily premature
children and even more so in

711
00:36:22,300 --> 00:36:25,840
places where the health care
might not be so good.

712
00:36:25,840 --> 00:36:27,980
So twins are, in general,
weaker.

713
00:36:27,980 --> 00:36:30,780
So if we go back to your point
and say, well, maybe the

714
00:36:30,780 --> 00:36:34,230
family size is the same at the
end between a family that has

715
00:36:34,230 --> 00:36:37,390
twins at first birth and a
single child at first birth,

716
00:36:37,390 --> 00:36:40,760
you end up with three
regardless, say, or two

717
00:36:40,760 --> 00:36:45,560
regardless, but there might
still be a difference between

718
00:36:45,560 --> 00:36:48,100
the twins and the non twins just
because the twins were

719
00:36:48,100 --> 00:36:49,275
born weaker.

720
00:36:49,275 --> 00:36:50,990
AUDIENCE: Can't you
account for that?

721
00:36:50,990 --> 00:36:52,454
PROFESSOR: How?

722
00:36:52,454 --> 00:36:52,946
AUDIENCE: I don't know.

723
00:36:52,946 --> 00:36:57,866
If you have, like, data on the
average wealth of twins versus

724
00:36:57,866 --> 00:36:58,750
the average wealth--

725
00:36:58,750 --> 00:37:00,450
PROFESSOR: So it's not
only the wealth.

726
00:37:00,450 --> 00:37:02,550
The wealth would be the same.

727
00:37:02,550 --> 00:37:05,300
So you could adjust looking at
birth weight, for example.

728
00:37:05,300 --> 00:37:07,370
So some people have done that,
to look at the difference

729
00:37:07,370 --> 00:37:10,950
between twins and non twins
comparing for birth weight and

730
00:37:10,950 --> 00:37:14,410
assuming that birth weight
completely captured the fact

731
00:37:14,410 --> 00:37:18,950
that twins were in a more
adverse in utero environment.

732
00:37:18,950 --> 00:37:23,230
But another thing you can do
is to do what was suggested

733
00:37:23,230 --> 00:37:28,500
before which is to say, let's
look at that kid who was born,

734
00:37:28,500 --> 00:37:32,870
the first one, and then at the
second birth it gets either

735
00:37:32,870 --> 00:37:34,310
one sibling or two.

736
00:37:34,310 --> 00:37:38,070
And that's a shock
for him or her.

737
00:37:38,070 --> 00:37:39,960
And he or she is no different.

738
00:37:39,960 --> 00:37:44,300
It's the same child and the
first few years were in the

739
00:37:44,300 --> 00:37:45,020
same environment.

740
00:37:45,020 --> 00:37:47,810
But certainly there are these
two kids who are coming

741
00:37:47,810 --> 00:37:48,745
instead of one.

742
00:37:48,745 --> 00:37:50,240
So that gives you a shock.

743
00:37:50,240 --> 00:37:51,222
Yeah, Ben.

744
00:37:51,222 --> 00:37:52,695
AUDIENCE: Isn't it also
difficult to look at the

745
00:37:52,695 --> 00:37:56,132
relative treatment of the
children because there is no

746
00:37:56,132 --> 00:37:57,605
prior child to look at?

747
00:37:57,605 --> 00:38:01,777
But if we have twins in the
first trial, they're born at

748
00:38:01,777 --> 00:38:03,497
the same time, they're
the same age.

749
00:38:03,497 --> 00:38:06,443
You can't say one education--

750
00:38:06,443 --> 00:38:08,570
the parents did something
completely different than they

751
00:38:08,570 --> 00:38:10,410
would have done otherwise--

752
00:38:10,410 --> 00:38:11,250
PROFESSOR: Yes.

753
00:38:11,250 --> 00:38:14,970
So knowing what they would have
done is looking at the

754
00:38:14,970 --> 00:38:18,180
single child in other family
and saying that

755
00:38:18,180 --> 00:38:19,330
getting twins is random.

756
00:38:19,330 --> 00:38:22,350
So they would have treated them
like people generally

757
00:38:22,350 --> 00:38:24,100
treat their single children.

758
00:38:24,100 --> 00:38:26,600
But the problem is that probably
they wouldn't because

759
00:38:26,600 --> 00:38:29,360
they are twins and they're very
fragile, whereas if I

760
00:38:29,360 --> 00:38:33,030
look at the first child, the
first child is the same.

761
00:38:33,030 --> 00:38:38,690
But then he is in a family of
three or in the family of two.

762
00:38:38,690 --> 00:38:43,300
So there is a paper--

763
00:38:43,300 --> 00:38:46,000
so we went over gender--

764
00:38:46,000 --> 00:38:50,143
a paper by George Angrist,
Victor Lavy, and Eliot

765
00:38:50,143 --> 00:38:56,390
Schlosser looking at exploiting
the twinning and

766
00:38:56,390 --> 00:39:00,980
the gender differences, both the
sex mix and the fact that

767
00:39:00,980 --> 00:39:04,200
people prefer boys in Israel.

768
00:39:04,200 --> 00:39:05,790
Now, you might think Israel
is a rich country.

769
00:39:05,790 --> 00:39:07,930
Why do we care?

770
00:39:07,930 --> 00:39:10,130
Or we might care about Israel in
general, but why do we care

771
00:39:10,130 --> 00:39:11,880
in this class?

772
00:39:11,880 --> 00:39:15,170
Well, Israel is a rich country
but it also has poor people.

773
00:39:15,170 --> 00:39:18,400
And they are using pretty
much all of Israel.

774
00:39:18,400 --> 00:39:23,110
So it's very large samples,
including a large sample of

775
00:39:23,110 --> 00:39:26,750
poor people because they also
look at the Israeli Arabs

776
00:39:26,750 --> 00:39:30,620
which are getting to be as poor
as some of the people we

777
00:39:30,620 --> 00:39:33,010
look at in other countries.

778
00:39:33,010 --> 00:39:37,360
So they are looking at that in a
lot of detail, comparing the

779
00:39:37,360 --> 00:39:42,290
siblings of twins, first born,
when the second birth is a

780
00:39:42,290 --> 00:39:47,900
twin, comparing the children
born in different gender mix,

781
00:39:47,900 --> 00:39:51,040
and then putting all
of this together.

782
00:39:51,040 --> 00:39:56,000
And they find no effect at all
of larger family size.

783
00:39:56,000 --> 00:40:03,220
They find absolutely no adverse
impact of being born

784
00:40:03,220 --> 00:40:05,390
in a larger family.

785
00:40:05,390 --> 00:40:09,640
That is a bit surprising since,
again, I think most

786
00:40:09,640 --> 00:40:12,700
people would have expected
large effect.

787
00:40:12,700 --> 00:40:16,790
So you can think, OK, maybe it's
Israel and even Israeli

788
00:40:16,790 --> 00:40:20,370
Arabs live in an environment
where they are poor but they

789
00:40:20,370 --> 00:40:21,670
can go to school for free.

790
00:40:21,670 --> 00:40:23,570
They can get good health care.

791
00:40:23,570 --> 00:40:26,160
So maybe we don't see the
quality quantity trade off in

792
00:40:26,160 --> 00:40:29,932
this context because these
are Israeli Arabs.

793
00:40:29,932 --> 00:40:33,605
So let's look at other places.

794
00:40:33,605 --> 00:40:38,300
Well, in obvious other places
the one-child policy where the

795
00:40:38,300 --> 00:40:43,560
state forces you to
have fewer kids.

796
00:40:43,560 --> 00:40:48,230
So here there is a paper by
Nancy Chen, who interestingly

797
00:40:48,230 --> 00:40:51,490
is a student of George Angrist,
former student, who

798
00:40:51,490 --> 00:40:54,980
looks at the one child policy.

799
00:40:54,980 --> 00:40:56,780
So that's pretty clear,
the one child policy.

800
00:40:56,780 --> 00:40:59,790
Either you can have a second
child or you cannot.

801
00:40:59,790 --> 00:41:06,410
And I mentioned that since the
mid 1980s, some areas allow

802
00:41:06,410 --> 00:41:10,600
you to have a second child if
your first one was a girl,

803
00:41:10,600 --> 00:41:15,830
which means that if you want a
girl in an area that relaxed

804
00:41:15,830 --> 00:41:19,620
the policy, after the relaxation
policy was put in

805
00:41:19,620 --> 00:41:22,920
place then you're more likely
to have a sibling than if

806
00:41:22,920 --> 00:41:26,060
you're born a girl in a non
relaxed area or if you are

807
00:41:26,060 --> 00:41:28,030
born a boy in a relaxed area.

808
00:41:28,030 --> 00:41:29,480
So she exploits that.

809
00:41:29,480 --> 00:41:31,670
And you're very much more likely
because pretty much

810
00:41:31,670 --> 00:41:34,560
everyone who had a chance to
have a second child did.

811
00:41:34,560 --> 00:41:36,360
A lot of people did.

812
00:41:36,360 --> 00:41:38,630
So what do we find?

813
00:41:38,630 --> 00:41:45,740
This is a graph that tells you
the number of siblings that

814
00:41:45,740 --> 00:41:52,810
the child has as a function of
whether they were born and

815
00:41:52,810 --> 00:41:56,590
whether they were born
in a relaxed area.

816
00:41:56,590 --> 00:42:01,960
So this is the difference
between the family size.

817
00:42:01,960 --> 00:42:07,370
This is the difference between
the number of siblings that

818
00:42:07,370 --> 00:42:11,490
the girl has in a relaxed area
versus non relaxed area.

819
00:42:11,490 --> 00:42:13,250
So not all the areas relaxed.

820
00:42:13,250 --> 00:42:19,610
And the areas that relaxed,
the 1978, 1970s, because

821
00:42:19,610 --> 00:42:22,350
before they didn't have
a one-child policy.

822
00:42:22,350 --> 00:42:26,110
So what you find is that before
the one-child policy,

823
00:42:26,110 --> 00:42:29,720
there is not much difference
between the number of siblings

824
00:42:29,720 --> 00:42:33,500
that the girls have in area that
eventually will relax the

825
00:42:33,500 --> 00:42:37,440
policy because there is no such
policy in other area.

826
00:42:37,440 --> 00:42:41,560
So those places are
not fully random.

827
00:42:41,560 --> 00:42:47,050
But girls have an average of
maybe 0.50 more sibling in the

828
00:42:47,050 --> 00:42:50,620
relaxed areas before
the policy.

829
00:42:50,620 --> 00:42:55,740
And boys have 0.50 areas as
well, which shows us that they

830
00:42:55,740 --> 00:42:59,380
tended to allow people to relax
the policy in places

831
00:42:59,380 --> 00:43:01,760
which like children more.

832
00:43:01,760 --> 00:43:05,620
But what is interesting and
what's happening after, the

833
00:43:05,620 --> 00:43:08,850
relaxation of the policy
only affect the girls.

834
00:43:08,850 --> 00:43:12,750
So after the one-child policy,
you start seeing bigger and

835
00:43:12,750 --> 00:43:15,780
bigger difference between the
number of siblings that the

836
00:43:15,780 --> 00:43:20,440
girls have in a relaxed area
versus non relaxed area.

837
00:43:20,440 --> 00:43:27,920
And towards the end of the
period where most places

838
00:43:27,920 --> 00:43:32,060
passed the laws, a girl had an
average of about half more

839
00:43:32,060 --> 00:43:36,540
sibling in places that
did pass such a law.

840
00:43:36,540 --> 00:43:39,290
That means that every second
family who had a chance to

841
00:43:39,290 --> 00:43:43,720
have a another kid after
a girl had it.

842
00:43:43,720 --> 00:43:45,460
Zach.

843
00:43:45,460 --> 00:43:46,720
AUDIENCE: Wouldn't you expect
there to be a gap?

844
00:43:46,720 --> 00:43:50,070
In the places that relaxed the
policies, didn't they only

845
00:43:50,070 --> 00:43:54,267
relax the policies to have a
second child if the first one

846
00:43:54,267 --> 00:43:54,880
was a girl?

847
00:43:54,880 --> 00:43:55,580
PROFESSOR: Yeah.

848
00:43:55,580 --> 00:43:58,050
So it's exactly what
you would expect.

849
00:43:58,050 --> 00:44:05,570
So this is telling you that in
places which had relaxed area,

850
00:44:05,570 --> 00:44:08,130
that did have an effect, that
people took advantage.

851
00:44:08,130 --> 00:44:12,250
And if they had a girl as the
first born, they had a second

852
00:44:12,250 --> 00:44:15,580
child, whereas for the boys,
since that doesn't allow them

853
00:44:15,580 --> 00:44:17,920
to have when a policy, there
is no difference.

854
00:44:17,920 --> 00:44:18,610
So you're exactly right.

855
00:44:18,610 --> 00:44:19,800
This is exactly what
you would expect.

856
00:44:19,800 --> 00:44:21,540
It's not an interesting fact.

857
00:44:21,540 --> 00:44:24,180
It's just showing you that
the policy worked

858
00:44:24,180 --> 00:44:25,610
as you would expect.

859
00:44:25,610 --> 00:44:28,580
Now we're going to exploit that
to say is it the case

860
00:44:28,580 --> 00:44:32,260
that this first girl, who has
more siblings, is she less

861
00:44:32,260 --> 00:44:34,930
educated compared to what would
have been the case if

862
00:44:34,930 --> 00:44:35,900
she were a boy?

863
00:44:35,900 --> 00:44:38,590
So we are looking here at the
first stage, if you want.

864
00:44:38,590 --> 00:44:39,290
Yeah.

865
00:44:39,290 --> 00:44:40,830
AUDIENCE: So is this all looking
at the first borns and

866
00:44:40,830 --> 00:44:41,320
showing their--

867
00:44:41,320 --> 00:44:43,824
PROFESSOR: This is looking at
the number of siblings of the

868
00:44:43,824 --> 00:44:44,400
first born.

869
00:44:44,400 --> 00:44:46,990
So it's telling you that if
you're a girl, you're more

870
00:44:46,990 --> 00:44:49,770
likely to have a sibling if
you're born relaxed than non

871
00:44:49,770 --> 00:44:51,080
relaxed towards the
end of the period.

872
00:44:51,080 --> 00:44:53,650
But that's not the case for
boys, which is exactly what we

873
00:44:53,650 --> 00:44:54,728
would expect.

874
00:44:54,728 --> 00:44:56,680
Yep.

875
00:44:56,680 --> 00:44:59,120
AUDIENCE: Is all this data
from areas eventually

876
00:44:59,120 --> 00:45:00,590
[INAUDIBLE]?

877
00:45:00,590 --> 00:45:06,125
PROFESSOR: So each of these
points is the difference

878
00:45:06,125 --> 00:45:09,090
between all the places that will
eventually be relaxed and

879
00:45:09,090 --> 00:45:11,880
all the places that will
never be relaxed.

880
00:45:11,880 --> 00:45:14,910
So all these points are
already differences.

881
00:45:14,910 --> 00:45:19,930
But the reason why it keeps
increasing is that it's the

882
00:45:19,930 --> 00:45:23,340
difference between places that
will eventually be relaxed.

883
00:45:23,340 --> 00:45:25,780
And some of them got relaxed
only towards the end.

884
00:45:25,780 --> 00:45:28,330
And that's why the difference
keeps increasing.

885
00:45:28,330 --> 00:45:29,700
Does that make sense?

886
00:45:29,700 --> 00:45:31,160
So each of these is
a difference.

887
00:45:31,160 --> 00:45:35,000
And it's telling you that if you
look just at this point in

888
00:45:35,000 --> 00:45:39,100
1981, if you were a girl born
in a relaxed area, you had

889
00:45:39,100 --> 00:45:42,980
about half a sibling more than
if you were a girl born in a

890
00:45:42,980 --> 00:45:44,280
non relaxed area.

891
00:45:44,280 --> 00:45:48,640
But for boys, you had only a
tenth of a sibling more, like,

892
00:45:48,640 --> 00:45:50,340
strictly speaking, zero.

893
00:45:50,340 --> 00:45:53,320
So that is exactly right.

894
00:45:53,320 --> 00:45:55,410
There's nothing particularly
interesting there.

895
00:45:55,410 --> 00:45:58,840
That's just the basic fact that
we are going to rely on

896
00:45:58,840 --> 00:46:02,580
to now show we're going to run
the exact same analysis for

897
00:46:02,580 --> 00:46:06,130
the first born, not looking at
their number of siblings but

898
00:46:06,130 --> 00:46:08,240
looking at their education.

899
00:46:08,240 --> 00:46:11,980
So if having more siblings is
bad for your education, what

900
00:46:11,980 --> 00:46:14,520
would you expect the shape
of the equivalent

901
00:46:14,520 --> 00:46:17,280
of these red lines?

902
00:46:17,280 --> 00:46:19,960
It would be decreasing, because
the later you were

903
00:46:19,960 --> 00:46:24,580
born, the more likely that
you have one more kid.

904
00:46:24,580 --> 00:46:27,290
And, in fact, what do we find?

905
00:46:27,290 --> 00:46:31,040
We find that it's increasing,
and moreover it's increasing

906
00:46:31,040 --> 00:46:33,890
for girls but not for boys.

907
00:46:33,890 --> 00:46:37,620
So towards the end of the
period, girls born in relaxed

908
00:46:37,620 --> 00:46:42,610
area are actually more educated
than boys born in a

909
00:46:42,610 --> 00:46:44,750
relaxed area, compared
to what happened in

910
00:46:44,750 --> 00:46:46,010
a non relaxed area.

911
00:46:46,010 --> 00:46:46,470
Yeah.

912
00:46:46,470 --> 00:46:49,240
AUDIENCE: Can you help me
understand what the y-axis is?

913
00:46:49,240 --> 00:46:53,540
PROFESSOR: The y-axis here is
the difference in the years of

914
00:46:53,540 --> 00:46:55,970
education between the relaxed
and the non relaxed area.

915
00:46:55,970 --> 00:46:59,055
So it's saying that the relaxed
area, probably we are

916
00:46:59,055 --> 00:47:03,620
poor because the kids at the
beginning of the period tended

917
00:47:03,620 --> 00:47:06,990
to be less educated in a relaxed
and non relaxed area.

918
00:47:06,990 --> 00:47:10,324
And at the end of the period
it's towards zero.

919
00:47:10,324 --> 00:47:11,740
AUDIENCE: So the more kids
you have, the more

920
00:47:11,740 --> 00:47:13,820
education you have.

921
00:47:13,820 --> 00:47:13,950
PROFESSOR: Exactly.

922
00:47:13,950 --> 00:47:18,300
The more siblings you have, the
more education you get.

923
00:47:18,300 --> 00:47:20,710
Remember, it's not going
from one to eight.

924
00:47:20,710 --> 00:47:24,874
It's going from zero siblings to
half a chance of a sibling.

925
00:47:24,874 --> 00:47:25,862
Yeah.

926
00:47:25,862 --> 00:47:27,097
AUDIENCE: So how much
more education does

927
00:47:27,097 --> 00:47:27,838
that translate into?

928
00:47:27,838 --> 00:47:31,296
Because if, for instance, you
have a first child that is a

929
00:47:31,296 --> 00:47:35,576
girl and then you wait, say, six
years, so the child has a

930
00:47:35,576 --> 00:47:37,718
year of school, which
[INAUDIBLE] haven't gotten,

931
00:47:37,718 --> 00:47:40,682
and then you have a second
child, then you're still not

932
00:47:40,682 --> 00:47:42,658
actually trying to educate
your child anymore.

933
00:47:42,658 --> 00:47:47,310
You're just still investing in
the children that you have.

934
00:47:47,310 --> 00:47:48,621
PROFESSOR: Can you repeat
the question?

935
00:47:48,621 --> 00:47:51,101
AUDIENCE: I mean, if you have
two children, can't you say

936
00:47:51,101 --> 00:47:52,680
your [INAUDIBLE]

937
00:47:52,680 --> 00:47:53,350
goes to school?

938
00:47:53,350 --> 00:47:57,671
Whereas if you just were
stuck with one child--

939
00:47:57,671 --> 00:47:59,603
how do I explain this?

940
00:47:59,603 --> 00:48:02,946
And really does this show at all
that there was the intent

941
00:48:02,946 --> 00:48:05,386
to educate these girls
who were first born?

942
00:48:05,386 --> 00:48:09,778
Or does it just show that they
were investigating whether

943
00:48:09,778 --> 00:48:11,242
they'd have while they had it.

944
00:48:11,242 --> 00:48:12,706
And then once they got a second
boy, they started

945
00:48:12,706 --> 00:48:15,170
investing in the boy?

946
00:48:15,170 --> 00:48:17,340
PROFESSOR: So if this were in
the model then we would find

947
00:48:17,340 --> 00:48:20,900
the girls to be less educated
because once the boy comes--

948
00:48:20,900 --> 00:48:24,280
or at least as much-- because
once the boy comes then they

949
00:48:24,280 --> 00:48:26,930
start, you know, sharing the
resources or giving everything

950
00:48:26,930 --> 00:48:27,960
to the boy.

951
00:48:27,960 --> 00:48:31,790
It's good pointing out that
mostly the second kid is a boy

952
00:48:31,790 --> 00:48:35,060
because selective abortion of
the second child is horrible.

953
00:48:35,060 --> 00:48:36,820
Like, most of these second
kids are boys.

954
00:48:36,820 --> 00:48:37,788
Yep.

955
00:48:37,788 --> 00:48:42,144
AUDIENCE: So you were saying
that if you get another child

956
00:48:42,144 --> 00:48:44,564
[INAUDIBLE] schools that they
actually get more schooling,

957
00:48:44,564 --> 00:48:47,480
but with this school is that
they get just as much.

958
00:48:47,480 --> 00:48:50,520
PROFESSOR: Oh, well, this is the
idea of starting from the

959
00:48:50,520 --> 00:48:51,440
differences.

960
00:48:51,440 --> 00:48:55,080
So the idea is that those
regions were regions where

961
00:48:55,080 --> 00:49:00,320
before girls tended to
be less educated.

962
00:49:00,320 --> 00:49:03,200
And even the boys tended
to be less educated.

963
00:49:03,200 --> 00:49:05,760
And nothing really changed
for the boys.

964
00:49:05,760 --> 00:49:07,720
But for the girls it went up.

965
00:49:07,720 --> 00:49:10,180
So the point is these regions
that relaxed, they are not the

966
00:49:10,180 --> 00:49:14,480
same as the regions
that didn't relax.

967
00:49:14,480 --> 00:49:17,050
Those were poor or more
backwater regions where the

968
00:49:17,050 --> 00:49:19,150
problem of infanticide was
bigger or accepted

969
00:49:19,150 --> 00:49:19,780
[INAUDIBLE].

970
00:49:19,780 --> 00:49:21,740
That's why they relaxed.

971
00:49:21,740 --> 00:49:26,160
So that's why we are more
interested in the slope and

972
00:49:26,160 --> 00:49:29,070
how it looks at the end compared
to the beginning than

973
00:49:29,070 --> 00:49:30,610
the levels.

974
00:49:30,610 --> 00:49:32,370
So the levels are wherever
they are.

975
00:49:32,370 --> 00:49:35,000
And in particular what is very
interesting is that the girls

976
00:49:35,000 --> 00:49:39,660
tend to do better than the boys
in the relaxed areas,

977
00:49:39,660 --> 00:49:42,455
relatively better in the relaxed
area than the boys,

978
00:49:42,455 --> 00:49:49,850
which is saying that if you
have to be a girl, it is

979
00:49:49,850 --> 00:49:52,530
better to be a girl in the
relaxed area compared to being

980
00:49:52,530 --> 00:49:54,344
a boy in the relaxed area.

981
00:49:54,344 --> 00:49:55,320
AUDIENCE: I mean, it mean--

982
00:49:55,320 --> 00:49:57,760
[INAUDIBLE] anything about
Chinese culture-- it might

983
00:49:57,760 --> 00:50:03,128
mean that the parents that are
in these relaxed areas which

984
00:50:03,128 --> 00:50:06,300
might be in more rural areas,
they want to educate their

985
00:50:06,300 --> 00:50:09,569
girls more because they want to
then send them so that they

986
00:50:09,569 --> 00:50:10,448
can find a husband.

987
00:50:10,448 --> 00:50:14,832
If they have more education,
maybe they have more chance of

988
00:50:14,832 --> 00:50:17,230
getting a good husband.

989
00:50:17,230 --> 00:50:18,960
PROFESSOR: I think you're right,
except that this is

990
00:50:18,960 --> 00:50:22,130
what it's trying to account for,
which is, let's say from

991
00:50:22,130 --> 00:50:29,410
1973 to 1977 is when
the areas--

992
00:50:29,410 --> 00:50:32,440
there is no relaxation because
there is no policy yet.

993
00:50:32,440 --> 00:50:36,010
So this is saying that those
places, before the relaxation,

994
00:50:36,010 --> 00:50:40,420
girls tended to do much worse,
whereas after the relaxation

995
00:50:40,420 --> 00:50:42,870
they do somewhat better.

996
00:50:42,870 --> 00:50:44,625
[INAUDIBLE].

997
00:50:44,625 --> 00:50:49,080
AUDIENCE: I was wondering
whether this can be considered

998
00:50:49,080 --> 00:50:55,630
a good refutation of the quality
quantity credo because

999
00:50:55,630 --> 00:51:00,233
firstly when these people with
large family and position of

1000
00:51:00,233 --> 00:51:01,478
birth [INAUDIBLE]

1001
00:51:01,478 --> 00:51:04,964
is not quite the same as
having two children.

1002
00:51:04,964 --> 00:51:09,230
And, number two, we also need
to know whether there was a

1003
00:51:09,230 --> 00:51:11,660
cultural and infrastructural
change.

1004
00:51:11,660 --> 00:51:15,690
[INAUDIBLE] changing attitude
towards girl's education and

1005
00:51:15,690 --> 00:51:19,572
more schools perhaps in rural
areas, for which, you know,

1006
00:51:19,572 --> 00:51:23,448
girls always tend to pick up
any opportunity much better

1007
00:51:23,448 --> 00:51:25,250
than boys do.

1008
00:51:25,250 --> 00:51:26,452
PROFESSOR: Right.

1009
00:51:26,452 --> 00:51:28,250
So that's an excellent point.

1010
00:51:28,250 --> 00:51:31,430
Let me start with the second
point, whether things changed.

1011
00:51:31,430 --> 00:51:34,150
That's the advantage of
comparing the relaxed versus

1012
00:51:34,150 --> 00:51:34,640
non relaxed.

1013
00:51:34,640 --> 00:51:36,252
Things probably would
have changed in

1014
00:51:36,252 --> 00:51:38,170
parallel in the two places.

1015
00:51:38,170 --> 00:51:42,082
The first point is
quite important.

1016
00:51:42,082 --> 00:51:43,820
Yeah, that's a bit late.

1017
00:51:43,820 --> 00:51:45,506
You can't show up at 2:00.

1018
00:51:45,506 --> 00:51:47,298
Sorry.

1019
00:51:47,298 --> 00:51:49,790
The first point is very
important, which is it's not

1020
00:51:49,790 --> 00:51:51,090
going from six to seven.

1021
00:51:51,090 --> 00:51:53,500
It's really going
from one to two.

1022
00:51:53,500 --> 00:51:57,240
And so there are two things
that are relevant here,

1023
00:51:57,240 --> 00:52:00,310
something which you also kind
of alluded to earlier.

1024
00:52:00,310 --> 00:52:04,040
One is we know that being
a single child is

1025
00:52:04,040 --> 00:52:05,390
not that much fun.

1026
00:52:05,390 --> 00:52:08,130
And maybe going from one to two
is good, but going from

1027
00:52:08,130 --> 00:52:09,500
four to five is bad.

1028
00:52:09,500 --> 00:52:12,070
So maybe we are not learning
about what we're really

1029
00:52:12,070 --> 00:52:15,540
interested, which is whether
families would reduce from

1030
00:52:15,540 --> 00:52:22,980
five to three by looking at
the one to two phenomenon.

1031
00:52:22,980 --> 00:52:25,540
So that's very, very true.

1032
00:52:25,540 --> 00:52:30,210
The second thing is all of these
children are girls who

1033
00:52:30,210 --> 00:52:33,120
are acquiring a brother.

1034
00:52:33,120 --> 00:52:36,650
And in a culture which is not
very favorable to girls, it

1035
00:52:36,650 --> 00:52:39,870
might be very good to have a
brother for a girl because

1036
00:52:39,870 --> 00:52:42,070
then the family is going
to send the kid--

1037
00:52:42,070 --> 00:52:43,270
I think that's kind
of related to what

1038
00:52:43,270 --> 00:52:44,580
you were saying anyway.

1039
00:52:44,580 --> 00:52:47,930
The family's going to send
the little boy to school.

1040
00:52:47,930 --> 00:52:51,490
Well, I might as well send the
girl with the boy anyway.

1041
00:52:51,490 --> 00:52:54,250
You know, instead of competing
for the resources, people

1042
00:52:54,250 --> 00:52:55,650
actually drag themselves.

1043
00:52:55,650 --> 00:52:58,330
You need someone to bring the
boy to school and there you

1044
00:52:58,330 --> 00:52:59,330
have the older sister.

1045
00:52:59,330 --> 00:53:00,930
That's kind of convenient.

1046
00:53:00,930 --> 00:53:04,400
So what we're learning from
this may not be actually--

1047
00:53:04,400 --> 00:53:09,620
I think we are learning that
having second child, for girls

1048
00:53:09,620 --> 00:53:12,940
in China, having a brother
was actually a good deal.

1049
00:53:12,940 --> 00:53:15,710
But whether this is telling us
about the quality quantity

1050
00:53:15,710 --> 00:53:18,480
trade off more generally, I
think you're right to be

1051
00:53:18,480 --> 00:53:20,332
suspicious.

1052
00:53:20,332 --> 00:53:22,276
AUDIENCE: I was just wondering
if there's selection bias.

1053
00:53:22,276 --> 00:53:26,650
So for families that have the
boy first time around, is it

1054
00:53:26,650 --> 00:53:28,594
possible [INAUDIBLE]

1055
00:53:28,594 --> 00:53:31,024
going on?

1056
00:53:31,024 --> 00:53:34,440
So if there are two children,
it sort of shows that you

1057
00:53:34,440 --> 00:53:38,002
value girls and would be more
likely to send them to school.

1058
00:53:38,002 --> 00:53:39,330
Does that make sense at all?

1059
00:53:39,330 --> 00:53:39,730
PROFESSOR: Right.

1060
00:53:39,730 --> 00:53:39,910
Yes.

1061
00:53:39,910 --> 00:53:41,590
You might have this problem.

1062
00:53:41,590 --> 00:53:45,700
And it would become problem if
the selection bias changed

1063
00:53:45,700 --> 00:53:48,070
over time, which is at the
beginning you have no

1064
00:53:48,070 --> 00:53:50,450
selection bias because
there is no abortion.

1065
00:53:50,450 --> 00:53:52,740
Towards the end you have more
and more abortion so the

1066
00:53:52,740 --> 00:53:56,420
families that still have a girl
are the ones who care

1067
00:53:56,420 --> 00:53:58,020
more about girls.

1068
00:53:58,020 --> 00:53:59,670
And that could be different.

1069
00:53:59,670 --> 00:54:02,350
So the thing is that it should
be different in a relaxed and

1070
00:54:02,350 --> 00:54:04,660
non relaxed area to
create a problem.

1071
00:54:04,660 --> 00:54:06,910
But if we are thinking that
the relaxed areas are the

1072
00:54:06,910 --> 00:54:13,710
areas where the bias was the
worse to start with then this

1073
00:54:13,710 --> 00:54:17,670
bias gets more and more chances
to express itself over

1074
00:54:17,670 --> 00:54:20,080
time because the abortion
becomes available.

1075
00:54:20,080 --> 00:54:22,900
And so that might also
create a bias.

1076
00:54:22,900 --> 00:54:26,020
So these two points are
both excellent points.

1077
00:54:26,020 --> 00:54:27,060
But they are different points.

1078
00:54:27,060 --> 00:54:30,950
One is that these might be a
bias in estimating the effect.

1079
00:54:30,950 --> 00:54:34,420
And yours is a point about the
interpretation, which I think

1080
00:54:34,420 --> 00:54:36,510
is quite valid.

1081
00:54:36,510 --> 00:54:38,323
[INAUDIBLE].

1082
00:54:38,323 --> 00:54:40,041
AUDIENCE: This doesn't tell us
anything about average levels

1083
00:54:40,041 --> 00:54:41,680
of education again,
though, right?.

1084
00:54:41,680 --> 00:54:42,060
PROFESSOR: No.

1085
00:54:42,060 --> 00:54:42,980
This is all in differences.

1086
00:54:42,980 --> 00:54:43,265
AUDIENCE: Yeah.

1087
00:54:43,265 --> 00:54:48,082
So if girls get, say, a year
of education now where they

1088
00:54:48,082 --> 00:54:52,491
got zero years of education
before, the difference is made

1089
00:54:52,491 --> 00:54:54,800
up, whereas boys get, say,
10 years of education.

1090
00:54:54,800 --> 00:54:55,070
PROFESSOR: Absolutely.

1091
00:54:55,070 --> 00:54:56,510
This tells you nothing
about the difference

1092
00:54:56,510 --> 00:54:57,910
between girls and boys.

1093
00:54:57,910 --> 00:55:01,830
This tells you that whatever
this difference was and

1094
00:55:01,830 --> 00:55:03,150
whatever this difference--

1095
00:55:03,150 --> 00:55:06,480
it used to be bigger.

1096
00:55:06,480 --> 00:55:09,380
Girls used to be more
disadvantaged in the relaxed

1097
00:55:09,380 --> 00:55:12,774
areas before the relaxation
happened and after.

1098
00:55:12,774 --> 00:55:14,619
AUDIENCE: I was just thinking,
if for boys there was no

1099
00:55:14,619 --> 00:55:16,710
change but boys were still
getting a high level of

1100
00:55:16,710 --> 00:55:19,662
education, this doesn't
really say anything.

1101
00:55:19,662 --> 00:55:22,614
But also if girls who were
getting zero education now are

1102
00:55:22,614 --> 00:55:25,580
getting one year, that also
doesn't seem that significant.

1103
00:55:25,580 --> 00:55:26,680
PROFESSOR: Right.

1104
00:55:26,680 --> 00:55:30,440
That is always like whatever
the outcome versus the-- it

1105
00:55:30,440 --> 00:55:33,730
turns out, I think, that in
China once they're born, it's

1106
00:55:33,730 --> 00:55:38,450
not that girls get very
different level of education.

1107
00:55:38,450 --> 00:55:42,570
So in that sense, I don't know
what the levels are.

1108
00:55:42,570 --> 00:55:44,730
But I don't think they're quite
different to start with.

1109
00:55:44,730 --> 00:55:46,540
So those are all excellent
points.

1110
00:55:46,540 --> 00:55:52,180
So all that to say that
maybe this is--

1111
00:55:52,180 --> 00:55:53,560
I agree with you.

1112
00:55:53,560 --> 00:55:55,200
In fact, I put [INAUDIBLE]

1113
00:55:55,200 --> 00:55:56,460
point on the slide.

1114
00:55:56,460 --> 00:55:58,100
Your other points were
also well taken.

1115
00:55:58,100 --> 00:55:59,520
Maybe that's not the
end of the world.

1116
00:55:59,520 --> 00:56:02,100
That's not the end
of the story.

1117
00:56:02,100 --> 00:56:04,070
This is definitely probably
the opposite of what would

1118
00:56:04,070 --> 00:56:04,800
have been expected.

1119
00:56:04,800 --> 00:56:06,110
I'm sure it's quite the
opposite of what

1120
00:56:06,110 --> 00:56:08,490
she expected to find.

1121
00:56:08,490 --> 00:56:11,980
So here is one more normal
example where it's not the one

1122
00:56:11,980 --> 00:56:13,270
child policy.

1123
00:56:13,270 --> 00:56:16,580
We are not forcing you to abort
the child that you don't

1124
00:56:16,580 --> 00:56:18,420
like the gender of, et cetera.

1125
00:56:18,420 --> 00:56:24,140
That's the ICDDR,B program in
Bangladesh where they provided

1126
00:56:24,140 --> 00:56:27,370
women in treatment areas
with regular access to

1127
00:56:27,370 --> 00:56:30,040
contraceptives, a community
health worker that visits

1128
00:56:30,040 --> 00:56:32,450
women at home regularly,
et cetera.

1129
00:56:32,450 --> 00:56:35,280
And they did this program
pretty constantly

1130
00:56:35,280 --> 00:56:37,125
since the late '70s.

1131
00:56:37,125 --> 00:56:41,160
It went on and on and on and
it's still going on today.

1132
00:56:41,160 --> 00:56:44,730
And that program was effective
after really insisting, very

1133
00:56:44,730 --> 00:56:47,440
effective in reducing the
number of children.

1134
00:56:47,440 --> 00:56:51,070
At the beginning it was
the most effective.

1135
00:56:51,070 --> 00:56:55,540
And then this effectiveness
went down, not because the

1136
00:56:55,540 --> 00:56:58,980
number of birth increased a lot
in the program area, but

1137
00:56:58,980 --> 00:57:01,620
because the number of birth
declined everywhere and

1138
00:57:01,620 --> 00:57:04,650
everywhere in Bangladesh very
fast during the period.

1139
00:57:04,650 --> 00:57:07,040
So at the end of the day the
effectiveness of this program

1140
00:57:07,040 --> 00:57:09,370
is a bit contested in that it
might just have accelerated a

1141
00:57:09,370 --> 00:57:11,150
trend that would have
happened anyway.

1142
00:57:11,150 --> 00:57:15,450
But regardless, it provides us a
good window into what is the

1143
00:57:15,450 --> 00:57:20,380
effect of a smaller family
because by 1996 women in

1144
00:57:20,380 --> 00:57:25,130
treatment area had 1.2 fewer
children than women in the

1145
00:57:25,130 --> 00:57:27,750
control area, out
of an average of

1146
00:57:27,750 --> 00:57:30,450
perhaps four or five.

1147
00:57:30,450 --> 00:57:32,800
So that's not an insignificant
change.

1148
00:57:32,800 --> 00:57:36,650
And there we are very much
closer to the type of

1149
00:57:36,650 --> 00:57:40,070
evaluation that you wanted to
see, which is if I reduce from

1150
00:57:40,070 --> 00:57:45,100
five to four, do I see a
difference in the outcomes?

1151
00:57:45,100 --> 00:57:48,310
Another thing the program did
is to provide very good

1152
00:57:48,310 --> 00:57:51,120
prenatal and postnatal
care to the kids.

1153
00:57:51,120 --> 00:57:54,100
Immunization, oral rehydration
solution,

1154
00:57:54,100 --> 00:57:55,720
et cetera, et cetera.

1155
00:57:55,720 --> 00:57:59,080
So one outcome that you don't
get is that kids are much more

1156
00:57:59,080 --> 00:58:01,160
likely to die in infancy.

1157
00:58:01,160 --> 00:58:02,440
That's fine.

1158
00:58:02,440 --> 00:58:06,120
But that may not be an effect
of having fewer families

1159
00:58:06,120 --> 00:58:07,640
because all these external
inputs were

1160
00:58:07,640 --> 00:58:09,780
given at the same time.

1161
00:58:09,780 --> 00:58:14,730
In 1996, a group of researchers
led by [? RAND ?]

1162
00:58:14,730 --> 00:58:18,470
went back to the area and did
a very detailed survey of

1163
00:58:18,470 --> 00:58:20,310
everybody living in both
treatment and control

1164
00:58:20,310 --> 00:58:23,830
villages, which is available
on the web.

1165
00:58:23,830 --> 00:58:26,420
So that is something
which people can--

1166
00:58:26,420 --> 00:58:28,610
if we want to do, like,
undergraduate projects or

1167
00:58:28,610 --> 00:58:30,670
whatever involving data, that
should be a good source of

1168
00:58:30,670 --> 00:58:32,670
data, very rich.

1169
00:58:32,670 --> 00:58:35,880
And first they look, of course,
is to look at whether

1170
00:58:35,880 --> 00:58:39,450
you find any affect on the
quality of the children who

1171
00:58:39,450 --> 00:58:42,600
were born during this period
in treatment area and in

1172
00:58:42,600 --> 00:58:45,090
control area, given that in
treatment they lived in a much

1173
00:58:45,090 --> 00:58:46,790
smaller family.

1174
00:58:46,790 --> 00:58:49,600
And what they find is no
difference, no difference in

1175
00:58:49,600 --> 00:58:52,900
height, no difference in weight,
no difference in

1176
00:58:52,900 --> 00:58:55,770
school enrollment, no difference
in years of

1177
00:58:55,770 --> 00:58:58,470
education, nothing.

1178
00:58:58,470 --> 00:59:01,900
So, again, here it's your most,
like, kind of classical

1179
00:59:01,900 --> 00:59:07,640
example of effective population
control of family.

1180
00:59:07,640 --> 00:59:10,240
A lot of the argument that you
guys discussed in the context

1181
00:59:10,240 --> 00:59:13,970
of the one child policy
can't really be made.

1182
00:59:13,970 --> 00:59:14,930
It's not Israel.

1183
00:59:14,930 --> 00:59:16,860
We can't say it's a rich
country that is able to

1184
00:59:16,860 --> 00:59:18,080
educate all these kids.

1185
00:59:18,080 --> 00:59:19,870
And, again, we find no effect.

1186
00:59:19,870 --> 00:59:20,830
Yeah.

1187
00:59:20,830 --> 00:59:22,750
AUDIENCE: I thought this was
really interesting because it

1188
00:59:22,750 --> 00:59:24,190
kind of ties into what
we've discussed

1189
00:59:24,190 --> 00:59:26,920
throughout the class.

1190
00:59:26,920 --> 00:59:30,385
I thought there has to be more
inputs into this equation.

1191
00:59:30,385 --> 00:59:34,345
So if students or parents are
more educated on the effects

1192
00:59:34,345 --> 00:59:38,800
of how their children could
potentially benefit from more

1193
00:59:38,800 --> 00:59:42,760
years of education then you
would expect if they reduce

1194
00:59:42,760 --> 00:59:44,575
the number of children, the
children would get more years

1195
00:59:44,575 --> 00:59:45,235
of education.

1196
00:59:45,235 --> 00:59:47,710
But if the parents weren't
necessarily educated on that

1197
00:59:47,710 --> 00:59:49,937
and didn't see the benefits
of it, then they just may

1198
00:59:49,937 --> 00:59:54,310
substitute away from the
research they would expend on

1199
00:59:54,310 --> 00:59:57,170
an additional child
[INAUDIBLE]

1200
00:59:57,170 --> 00:59:57,570
or--

1201
00:59:57,570 --> 00:59:58,370
I don't know.

1202
00:59:58,370 --> 01:00:01,810
Something other than the things
we're looking at here.

1203
01:00:01,810 --> 01:00:01,980
PROFESSOR: Exactly.

1204
01:00:01,980 --> 01:00:05,980
So one possibility is that
that's going back to the

1205
01:00:05,980 --> 01:00:08,820
argument we are making about
Malthus is maybe the pie is

1206
01:00:08,820 --> 01:00:11,860
actually not fixed because as
you have more children, well,

1207
01:00:11,860 --> 01:00:14,720
you're going to spend more
money on the children.

1208
01:00:14,720 --> 01:00:16,650
And as you have fewer children,
you're spending less

1209
01:00:16,650 --> 01:00:21,090
money on the children so that
what determines how much you

1210
01:00:21,090 --> 01:00:25,090
decide to invest in the child is
less the number of children

1211
01:00:25,090 --> 01:00:28,080
you have total but what you
think the returns to this

1212
01:00:28,080 --> 01:00:30,550
investment is going to be.

1213
01:00:30,550 --> 01:00:34,470
And another thing is that in a
lot of cases the investment

1214
01:00:34,470 --> 01:00:38,070
that we are talking about, they
are not so much money

1215
01:00:38,070 --> 01:00:42,540
because even in Bangladesh
school is largely free.

1216
01:00:42,540 --> 01:00:44,875
Maybe keeping a child, you know,
nourishing your child

1217
01:00:44,875 --> 01:00:45,940
is, of course, not free.

1218
01:00:45,940 --> 01:00:48,140
But it's not very, very
expensive compared to other

1219
01:00:48,140 --> 01:00:49,290
things you could do.

1220
01:00:49,290 --> 01:00:55,710
So maybe what we see is that
there is not so much of a

1221
01:00:55,710 --> 01:00:58,280
fixed budget constraint for
how much you can afford to

1222
01:00:58,280 --> 01:00:59,500
spend on your children.

1223
01:00:59,500 --> 01:01:02,070
But it's a whole family
constraint.

1224
01:01:02,070 --> 01:01:07,010
And what is determined in
children investment is less

1225
01:01:07,010 --> 01:01:09,950
how much money do you have or
how much time do you have, but

1226
01:01:09,950 --> 01:01:12,260
how you decide to allocate this
budget, which corresponds

1227
01:01:12,260 --> 01:01:16,580
more to the perception of cost
and benefits as we've seen in

1228
01:01:16,580 --> 01:01:19,580
all of our previous lectures.

1229
01:01:19,580 --> 01:01:21,440
So maybe you're right and maybe
we should have expected

1230
01:01:21,440 --> 01:01:23,530
that, and it just didn't
tie into things.

1231
01:01:23,530 --> 01:01:24,005
Yeah.

1232
01:01:24,005 --> 01:01:26,380
AUDIENCE: Maybe one way to look
at it is to look at the

1233
01:01:26,380 --> 01:01:30,068
effect on everyone else in the
family, like the parents.

1234
01:01:30,068 --> 01:01:33,175
Because, I guess, maybe a mom
would feed her children the

1235
01:01:33,175 --> 01:01:34,848
same as how many children
she has.

1236
01:01:34,848 --> 01:01:37,716
But, it would affect, like you
said, that overall budget

1237
01:01:37,716 --> 01:01:38,690
[INAUDIBLE].

1238
01:01:38,690 --> 01:01:42,112
PROFESSOR: So that is discussed
a little bit in the

1239
01:01:42,112 --> 01:01:42,390
chapter you read.

1240
01:01:42,390 --> 01:01:48,110
So what did people find when
they looked at the mothers?

1241
01:01:48,110 --> 01:01:49,700
AUDIENCE: The women in the
treatment areas ended

1242
01:01:49,700 --> 01:01:53,390
up with more jobs.

1243
01:01:53,390 --> 01:01:55,358
I don't remember if they
had [INAUDIBLE]

1244
01:01:55,358 --> 01:01:55,860
or not.

1245
01:01:55,860 --> 01:01:58,370
PROFESSOR: So in Matlab, what
you find is the mother in the

1246
01:01:58,370 --> 01:02:00,610
treatment areas are more
likely to work and

1247
01:02:00,610 --> 01:02:04,810
their BMI is higher.

1248
01:02:04,810 --> 01:02:09,180
And then there was this other
study from Colombia, which we

1249
01:02:09,180 --> 01:02:12,200
are going to see in a minute,
which showed a modest

1250
01:02:12,200 --> 01:02:17,050
reduction in the number of
children but also a lot of

1251
01:02:17,050 --> 01:02:18,900
effect on the timing of children
where people are

1252
01:02:18,900 --> 01:02:20,820
having children later.

1253
01:02:20,820 --> 01:02:25,140
And you find large effect on
women's education and woman's

1254
01:02:25,140 --> 01:02:27,330
job market participation.

1255
01:02:27,330 --> 01:02:31,680
So I think that's where you do
find it's exactly what you're

1256
01:02:31,680 --> 01:02:34,640
saying is happening, which is
that the pie expands and

1257
01:02:34,640 --> 01:02:36,750
contracts with the number
of children.

1258
01:02:36,750 --> 01:02:38,690
And, of course, something
else gives in.

1259
01:02:38,690 --> 01:02:43,169
But that's maybe the
mom for example.

1260
01:02:43,169 --> 01:02:46,620
AUDIENCE: One of the things that
was brought was the idea

1261
01:02:46,620 --> 01:02:50,071
that children are kind of used
like pension plans in a way.

1262
01:02:50,071 --> 01:02:54,508
And if you have less children
you save more [INAUDIBLE].

1263
01:02:54,508 --> 01:03:02,396
Has there been any studies
looking at difference in

1264
01:03:02,396 --> 01:03:05,600
governments, if it's more of a
socialist government and how

1265
01:03:05,600 --> 01:03:07,819
much social security
they give and then

1266
01:03:07,819 --> 01:03:09,820
relate that to fertility?

1267
01:03:09,820 --> 01:03:11,650
PROFESSOR: So it's
a great question.

1268
01:03:11,650 --> 01:03:15,240
And the quick answer to that
question is, surprisingly, no.

1269
01:03:15,240 --> 01:03:19,070
So if you've read the book
carefully, you notice that we

1270
01:03:19,070 --> 01:03:22,230
talked about the effect of
family planning and we talk

1271
01:03:22,230 --> 01:03:26,040
about the effect of culture or
social norms and stuff like

1272
01:03:26,040 --> 01:03:27,790
that, which I'm going
to do in a minute.

1273
01:03:27,790 --> 01:03:30,670
And then when we want to talk
about economics, we start

1274
01:03:30,670 --> 01:03:33,380
looking at the opposite research
is people who have

1275
01:03:33,380 --> 01:03:35,960
more children save less, or
people who have fewer

1276
01:03:35,960 --> 01:03:37,850
children save more.

1277
01:03:37,850 --> 01:03:40,660
So we switch the equation
suddenly, and therefore we

1278
01:03:40,660 --> 01:03:46,100
don't provide evidence that if
there is a Social Security

1279
01:03:46,100 --> 01:03:49,810
introduced or better insurance,
essentially people

1280
01:03:49,810 --> 01:03:51,150
have to fewer children.

1281
01:03:51,150 --> 01:03:56,410
We make the argument, but we
actually have no study that

1282
01:03:56,410 --> 01:03:57,380
directly supports
this argument.

1283
01:03:57,380 --> 01:04:00,070
We only have the opposite
studies, that people who have

1284
01:04:00,070 --> 01:04:02,940
fewer children save more.

1285
01:04:02,940 --> 01:04:04,160
And so that is likely.

1286
01:04:04,160 --> 01:04:07,230
That, I think, actually would
be a very nice study to do.

1287
01:04:13,270 --> 01:04:19,300
So that was for the first part
of the argument that large

1288
01:04:19,300 --> 01:04:21,120
families are bad.

1289
01:04:21,120 --> 01:04:27,340
And so by the end of whatever
literature there is right now,

1290
01:04:27,340 --> 01:04:30,590
we are yet to see any smoking
gun for that one.

1291
01:04:30,590 --> 01:04:34,750
The second part of the argument
is people cannot

1292
01:04:34,750 --> 01:04:37,850
control their fertility.

1293
01:04:37,850 --> 01:04:41,930
The not so nice version is the
cartoon I showed you where

1294
01:04:41,930 --> 01:04:44,040
basically they can't control
their fertility because they

1295
01:04:44,040 --> 01:04:45,310
are idiots.

1296
01:04:45,310 --> 01:04:48,420
And the nicer version, at least
the more politically

1297
01:04:48,420 --> 01:04:51,130
correct version, is they can't
control their fertility

1298
01:04:51,130 --> 01:04:54,160
because access to contraception
is difficult.

1299
01:04:54,160 --> 01:04:56,590
So let's test that.

1300
01:04:56,590 --> 01:04:58,900
What's the impact of making
contraceptive available on

1301
01:04:58,900 --> 01:05:01,450
reducing family size?

1302
01:05:01,450 --> 01:05:03,310
I mentioned that program
a moment ago.

1303
01:05:03,310 --> 01:05:05,680
It's a program that was
introduced by Colombia by a

1304
01:05:05,680 --> 01:05:06,450
young doctor.

1305
01:05:06,450 --> 01:05:07,780
Well, eventually he aged.

1306
01:05:07,780 --> 01:05:10,070
But in the beginning
he was young.

1307
01:05:10,070 --> 01:05:11,550
There was nothing before him.

1308
01:05:11,550 --> 01:05:14,950
And there was a big reduction
in fertility in Colombia

1309
01:05:14,950 --> 01:05:19,070
between the time that he
introduced his program and

1310
01:05:19,070 --> 01:05:21,150
when it was fully expended.

1311
01:05:21,150 --> 01:05:24,275
Fertility in Colombia
reduced from about--

1312
01:05:27,390 --> 01:05:29,450
you must remember that I showed
it yesterday-- seven

1313
01:05:29,450 --> 01:05:34,240
children per woman to about
three children per woman

1314
01:05:34,240 --> 01:05:37,190
between the 1960s
and the 1990s.

1315
01:05:37,190 --> 01:05:38,900
Now, fertility declined
in all of the

1316
01:05:38,900 --> 01:05:40,490
Latin American countries.

1317
01:05:40,490 --> 01:05:42,780
But it declined much
faster in Colombia.

1318
01:05:42,780 --> 01:05:45,040
Colombia used to be the country
in Latin America with

1319
01:05:45,040 --> 01:05:47,410
the highest number of
children per woman.

1320
01:05:47,410 --> 01:05:50,180
And it switched to being the one
with the lowest number of

1321
01:05:50,180 --> 01:05:52,290
children per woman.

1322
01:05:52,290 --> 01:05:55,110
I think it was the second
highest, and went to become

1323
01:05:55,110 --> 01:05:56,550
the second lowest.

1324
01:05:56,550 --> 01:05:59,560
So is it due to the program?

1325
01:05:59,560 --> 01:06:00,850
Of course, many other
things happened in

1326
01:06:00,850 --> 01:06:01,810
Colombia at that time.

1327
01:06:01,810 --> 01:06:04,730
So it may or may not be
due to the program.

1328
01:06:04,730 --> 01:06:11,270
So to look at the effect, young
professor in Stanford

1329
01:06:11,270 --> 01:06:15,305
named Grant Miller looked at the
way the program expanded.

1330
01:06:15,305 --> 01:06:20,140
And what he argued is that the
doctor had limited resources

1331
01:06:20,140 --> 01:06:22,210
and he didn't have a strong view
about where the program

1332
01:06:22,210 --> 01:06:24,320
should be put in place because
he wanted the program to be

1333
01:06:24,320 --> 01:06:26,730
put in place everywhere
anyway.

1334
01:06:26,730 --> 01:06:29,920
So whenever he had a chance
somewhere, he would go.

1335
01:06:29,920 --> 01:06:33,910
So what he argues is that we
can compare women who had

1336
01:06:33,910 --> 01:06:36,510
access to women who didn't have
access at various periods

1337
01:06:36,510 --> 01:06:38,100
in their life.

1338
01:06:38,100 --> 01:06:42,190
And then because maybe you don't
want to fully believe

1339
01:06:42,190 --> 01:06:44,420
this argument, he says,
well, that's fine.

1340
01:06:44,420 --> 01:06:49,060
Let's also look at how has
this changed over time.

1341
01:06:49,060 --> 01:06:56,160
So let's compare a woman who was
born later in the places

1342
01:06:56,160 --> 01:06:59,650
that got the family program
later to a woman who was born

1343
01:06:59,650 --> 01:07:02,560
earlier in a place that got
the family program later.

1344
01:07:02,560 --> 01:07:05,020
So the second woman didn't get
to benefit from the program,

1345
01:07:05,020 --> 01:07:06,035
and the first did.

1346
01:07:06,035 --> 01:07:09,300
And if you combine the two
sources of variation, you get

1347
01:07:09,300 --> 01:07:12,950
some idea of what was the effect
of the family planning

1348
01:07:12,950 --> 01:07:16,840
program, very much like the same
kind of strategy that we

1349
01:07:16,840 --> 01:07:21,350
used for the one child
policy in China.

1350
01:07:21,350 --> 01:07:25,970
So here you have the results,
first in log number of births,

1351
01:07:25,970 --> 01:07:31,620
which telling you it's 11% fewer
children per woman who

1352
01:07:31,620 --> 01:07:33,410
got family planning access.

1353
01:07:33,410 --> 01:07:36,170
Maybe it's easier to look at
this one, which is a number of

1354
01:07:36,170 --> 01:07:39,880
birth of kids born to a woman.

1355
01:07:39,880 --> 01:07:42,090
This is when you just
assume that the

1356
01:07:42,090 --> 01:07:42,690
program is randomly assigned.

1357
01:07:42,690 --> 01:07:46,962
So compare places which got the
program early to places

1358
01:07:46,962 --> 01:07:48,150
that got the program later.

1359
01:07:48,150 --> 01:07:51,960
This is controlling for inherent
differences by using

1360
01:07:51,960 --> 01:07:53,105
the expansion.

1361
01:07:53,105 --> 01:07:56,880
Now, it's also very similar, so
we can focus on this one.

1362
01:07:56,880 --> 01:07:59,650
And that tells you that having
access to the program when you

1363
01:07:59,650 --> 01:08:01,920
were young does have an effect,

1364
01:08:01,920 --> 01:08:03,330
very significant effect.

1365
01:08:03,330 --> 01:08:08,690
That's the t-statistic,
6.4% divided by 0.004.

1366
01:08:08,690 --> 01:08:11,010
The t-statistic is
through the roof.

1367
01:08:11,010 --> 01:08:12,810
That's extremely significant.

1368
01:08:12,810 --> 01:08:17,000
Shows you that a woman who had
access to the family planning

1369
01:08:17,000 --> 01:08:24,550
when she was 15 to 19 had about
6.4% fewer children.

1370
01:08:24,550 --> 01:08:26,390
So that's very significant.

1371
01:08:26,390 --> 01:08:29,420
But is it very large?

1372
01:08:29,420 --> 01:08:30,279
It's very, very small.

1373
01:08:30,279 --> 01:08:34,380
It's less than one tenths
of a child per woman.

1374
01:08:34,380 --> 01:08:36,750
So it's like that much.

1375
01:08:36,750 --> 01:08:37,330
[LAUGHTER]

1376
01:08:37,330 --> 01:08:39,490
PROFESSOR: That's not a
big part of a child.

1377
01:08:39,490 --> 01:08:41,700
So it's not a very big effect,
even though it's very

1378
01:08:41,700 --> 01:08:43,350
precisely estimated.

1379
01:08:43,350 --> 01:08:46,910
The biggest effect are obtained
for teen, people who

1380
01:08:46,910 --> 01:08:49,500
got the program when they were
a teen and then a few when

1381
01:08:49,500 --> 01:08:54,270
they were 20 to 24 and 25 to
29 and then, of course, the

1382
01:08:54,270 --> 01:08:59,300
effect become lower because
after 35 most people are

1383
01:08:59,300 --> 01:09:02,140
finished, have completed
their fertility.

1384
01:09:02,140 --> 01:09:05,390
So what this tells us is, yes,
there is an effect of getting

1385
01:09:05,390 --> 01:09:06,550
access to contraception.

1386
01:09:06,550 --> 01:09:08,346
But it's tiny.

1387
01:09:08,346 --> 01:09:09,479
It's tiny, tiny.

1388
01:09:09,479 --> 01:09:13,120
It's like 5% of a child.

1389
01:09:13,120 --> 01:09:15,979
That's not a big
effect at all.

1390
01:09:15,979 --> 01:09:19,670
And, in fact, that corresponds
to a very small part of the

1391
01:09:19,670 --> 01:09:23,420
overall trend in fertility
reduction in Colombia at the

1392
01:09:23,420 --> 01:09:27,130
time, about 1/10,
maximum 1/10.

1393
01:09:27,130 --> 01:09:31,130
So this wasn't a
very big deal.

1394
01:09:31,130 --> 01:09:33,340
So was this unique?

1395
01:09:33,340 --> 01:09:35,290
It was not very unique.

1396
01:09:35,290 --> 01:09:38,760
Other program was submitted in
Indonesia which varies the

1397
01:09:38,760 --> 01:09:42,109
same type of idea, found
no effect at all.

1398
01:09:42,109 --> 01:09:45,109
But I already spoke to you about
the Matlab the ICDDR,B

1399
01:09:45,109 --> 01:09:47,020
program in Bangladesh.

1400
01:09:47,020 --> 01:09:51,029
Matlab is not only a software
program, it's also a place,

1401
01:09:51,029 --> 01:09:55,510
which is the place where
they did this program.

1402
01:09:55,510 --> 01:09:59,740
And in Matlab I just told you
that the fertility got reduced

1403
01:09:59,740 --> 01:10:01,670
by the program.

1404
01:10:01,670 --> 01:10:04,800
But there's two points
to make about Matlab.

1405
01:10:04,800 --> 01:10:12,240
Number one, it was a very
intensive program where

1406
01:10:12,240 --> 01:10:15,640
someone came to the house
every other week.

1407
01:10:15,640 --> 01:10:18,260
It's also a place where a lot of
women were in [INAUDIBLE].

1408
01:10:18,260 --> 01:10:22,010
So they were not allowed to
get outside of the home.

1409
01:10:22,010 --> 01:10:24,230
So it was harder for them to
access the contraception or

1410
01:10:24,230 --> 01:10:27,010
even to know that it
was available.

1411
01:10:27,010 --> 01:10:30,680
And this community health worker
was very dynamic, very

1412
01:10:30,680 --> 01:10:33,700
forward young women that were
going to everybody's family

1413
01:10:33,700 --> 01:10:36,310
and really trying to
convince them.

1414
01:10:36,310 --> 01:10:39,090
So you would think that the
Matlab program is something

1415
01:10:39,090 --> 01:10:40,560
else than access.

1416
01:10:40,560 --> 01:10:43,390
It's also changing people's
preferences.

1417
01:10:43,390 --> 01:10:44,880
That's point number one.

1418
01:10:44,880 --> 01:10:49,155
Point number two, as I was
saying a minute ago, initially

1419
01:10:49,155 --> 01:10:50,960
the effects were very large.

1420
01:10:50,960 --> 01:10:53,985
But then the effect in
differences between treatment

1421
01:10:53,985 --> 01:10:57,150
and control decline and decline
and decline because

1422
01:10:57,150 --> 01:11:00,580
everywhere in Bangladesh,
including in the control area,

1423
01:11:00,580 --> 01:11:02,530
fertility declined anyway.

1424
01:11:02,530 --> 01:11:06,050
So this is an extremely
expensive program, which by

1425
01:11:06,050 --> 01:11:09,280
the end of the day just
accelerated a trend that

1426
01:11:09,280 --> 01:11:12,020
happened in Bangladesh where the
reduction in fertility was

1427
01:11:12,020 --> 01:11:14,875
huge over the period and seemed
to have very little to

1428
01:11:14,875 --> 01:11:16,920
do with this program but
everything to do with other

1429
01:11:16,920 --> 01:11:19,560
things that were happening
in Bangladesh.

1430
01:11:19,560 --> 01:11:29,050
So it seems that contraception
plays a role but not a very

1431
01:11:29,050 --> 01:11:33,620
big one, maybe an acceleration
role, maybe a small reduction

1432
01:11:33,620 --> 01:11:36,740
in fertility, maybe
a timing role.

1433
01:11:36,740 --> 01:11:38,840
Of course, that doesn't mean
that you don't want to have

1434
01:11:38,840 --> 01:11:42,390
contraception available because
it is much nicer to

1435
01:11:42,390 --> 01:11:45,750
control your fertility with
contraception than without.

1436
01:11:45,750 --> 01:11:47,610
And the timing is
also important.

1437
01:11:47,610 --> 01:11:51,340
So I'm not here advocating we
should stop spending any

1438
01:11:51,340 --> 01:11:53,240
effort trying to make
contraception available.

1439
01:11:53,240 --> 01:11:57,440
Just to say that as a population
control policy,

1440
01:11:57,440 --> 01:12:00,330
paradoxically it's pretty
ineffective, which means that

1441
01:12:00,330 --> 01:12:04,010
if you wanted to control family
planning policy, you

1442
01:12:04,010 --> 01:12:07,160
would have to understand why
people make the decision they

1443
01:12:07,160 --> 01:12:09,240
make because it seems that they
are able to make their

1444
01:12:09,240 --> 01:12:12,290
decision and then they
will stick to them.

1445
01:12:12,290 --> 01:12:14,230
And if you make contraception
available, they'll use the

1446
01:12:14,230 --> 01:12:15,660
contraception to
stick to them.

1447
01:12:15,660 --> 01:12:18,190
And if you don't, they'll
anyway find a way.

1448
01:12:18,190 --> 01:12:21,170
So we need to go further in
understanding the decision,

1449
01:12:21,170 --> 01:12:23,980
which we'll do next time.

1450
01:12:23,980 --> 01:12:26,198
You.

1451
01:12:26,198 --> 01:12:29,120
AUDIENCE: Just a small thought
that maybe it's possible that

1452
01:12:29,120 --> 01:12:31,392
as long as the program's in
place, everyone heard about

1453
01:12:31,392 --> 01:12:35,938
it, and this brought the subject
of not having as many

1454
01:12:35,938 --> 01:12:40,471
children closer to mind, and
that helped anyway despite not

1455
01:12:40,471 --> 01:12:41,710
directly helping.

1456
01:12:41,710 --> 01:12:41,990
PROFESSOR: Yes.

1457
01:12:41,990 --> 01:12:43,120
So we'll discuss that.

1458
01:12:43,120 --> 01:12:47,300
Except that I don't think the
discussion went much further.

1459
01:12:47,300 --> 01:12:49,620
In fact, there is a paper I will
discuss briefly next time

1460
01:12:49,620 --> 01:12:52,530
where the discussion
is very narrow.

1461
01:12:52,530 --> 01:12:55,400
It's like people from
you compound and you

1462
01:12:55,400 --> 01:12:56,320
discuss with them.

1463
01:12:56,320 --> 01:12:59,110
Even within treatment villages
we see the differences.

1464
01:12:59,110 --> 01:13:00,481
Yep.

1465
01:13:00,481 --> 01:13:01,699
AUDIENCE: I was
[? really flustered ?] in the

1466
01:13:01,699 --> 01:13:03,223
same thing.

1467
01:13:03,223 --> 01:13:05,845
Is that the kind of acceleration
that you're

1468
01:13:05,845 --> 01:13:06,835
talking about?

1469
01:13:06,835 --> 01:13:08,815
That, like, having this program
in place caused the

1470
01:13:08,815 --> 01:13:10,300
rest of the country to have--

1471
01:13:10,300 --> 01:13:12,470
PROFESSOR: No.

1472
01:13:12,470 --> 01:13:15,900
What I'm claiming is that if no
one had done any program in

1473
01:13:15,900 --> 01:13:19,610
Matlab, fertility in
Bangladesh would be

1474
01:13:19,610 --> 01:13:21,080
today what it is.

1475
01:13:21,080 --> 01:13:23,570
Matlab is a very small place
that technically didn't effect

1476
01:13:23,570 --> 01:13:24,930
the rest of Bangladesh.

1477
01:13:24,930 --> 01:13:27,610
But what happened is that
it was faster in

1478
01:13:27,610 --> 01:13:30,260
Matlab because of the--

1479
01:13:30,260 --> 01:13:32,840
that said, both of you make a
good point about social norms

1480
01:13:32,840 --> 01:13:34,300
that may have shifted in part.

1481
01:13:34,300 --> 01:13:37,210
I think Matlab was too small to
make any big impact on the

1482
01:13:37,210 --> 01:13:38,370
rest of Bangladesh.

1483
01:13:38,370 --> 01:13:42,750
So what it did is that people
were running a race in the

1484
01:13:42,750 --> 01:13:43,370
family reduction.

1485
01:13:43,370 --> 01:13:46,970
And the Matlab people arrived
a little bit earlier.

1486
01:13:46,970 --> 01:13:48,730
But they didn't arrive
much faster.

1487
01:13:51,430 --> 01:13:53,604
You had a point?

1488
01:13:53,604 --> 01:13:54,572
AUDIENCE: [INAUDIBLE].

1489
01:13:54,572 --> 01:13:55,056
PROFESSOR: OK.

1490
01:13:55,056 --> 01:13:58,120
So we'll stop here and pick up
again on decisions next time.