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PROFESSOR: So I think we have a bit of background in mind.
So now I'm going to summarize this discussion, and start
asking about how do we go about answering some of the
questions that have come about?
So at the end of last lecture, we were left with our S-shaped
curve, and saying that whether or not there would be a
poverty trap was really dependent on the shape of the
curve that relates income today to income tomorrow.
And we gave sent out examples where it could go one way or
the other, or it could be that its S shape, it could be that
it's increasing but inverted L-shape.
And then one of you asked the question,
well, how do we know?
How do we even get about--
how do we get to know the shape of the curve?
This is not a question that is going to be solved
theoretically.
The debate we just had a moment ago suggested it won't
be solved theoretically.
Because, for example, take the question of whether if I give
you a bed net for free today, you're less likely to buy the
next one tomorrow.
It depends on whether the entitlement effect is more
important than the loaning effect.
And how will I know that?
There is no way for me to know it without
looking at the data.
And the question is, what's a good way to look at the data?
And today, we're going to look at one such way, which is a
way which is increasingly often used by development
economists, by policy makers, and which is the main approach
that we are using in the Poverty Action Lab, which is
the idea of on randomized evaluation.
So we'll start with our malaria example.
I'm going to use the malaria example, because we had the
debate, so we know the question we're asking.
I'm going to use that as our example.
But, of course, the point I'm making now are important
methodological points as well.
So what are we talking about?
We're talking about a pretty important thing.
Almost 900,000 people die of malaria every year, give and
take, most of them in Africa, most of them under five.
That's the biggest cause of under-five
mortality in the world.
Incidentally, you want to take every single statistic with a
big pinch of salt, because it's not that all the malaria
cases are recorded--
a lot of people who are not really diagnosed of malaria
and are told to be dead of malaria, so it could be a
gross overestimate or a gross underestimate.
But I think it's fair to say it's a lot of people, one way
or the other.
As we discussed, malaria is transmitted by mosquitoes who
carry the parasite from an infected person to an
uninfected person, mainly at dusk.
So sleeping under a bed net, particularly a bed net which
has insecticide woven into the fiber of the bed net is an
effective way to prevent mosquito bites, and therefore
to prevent the transmission of malaria.
And one thing that no one said, which was important, is
that there is two effects of sleeping under a bed net.
If you already don't have malaria, you're less likely to
catch it, because the mosquitoes can't bite you.
So this is a direct benefit that benefits you.
So when making the decision to buy or not buy a bed net when
making the decision to use the bed net or not to use it, you
are going to take this direct benefit into account, right?
But then there is another benefit which is the
externality, which is an indirect effect, which is, if
you already have malaria, someone else is less likely to
get it because they don't first bite you
and then bite them.
And this benefit, unless you're an incredibly
socially-minded person, is a benefit you don't take into
account when buying your bed net.
Because you don't care.
It's not you.
It's someone else.
But as society, we are trying to maybe adjust the individual
behavior to the social benefit.
There's one more thing which is important for us to keep in
mind, which is this externality is not linear.
So it could be that the externality is linear, which
is one more person who sleeps under a bed net, say half a
fewer percent is infected.
So it could be like the more bed nets you have, the less
malaria you have, but in a disproportional way.
But it turns out that it's not proportional.
The reason why it's not proportionally is because once
about half the population sleeps under the bed net, you
have something called hard immunity, which is that the
mosquitoes don't have time to bite someone else before
either the mosquito or the parasite dies.
So if you manage to cover about half of your population,
you don't even need to carry the other half.
I mean, it's better, but they already
benefit almost as much.
So the externality benefits are like this, if you want.
They're like, first they're linear, and then at some
point, they have a big jump in the externality benefits.
And then again, going from 80% to 85%, maybe less.
So that means that this would need to be reminding you of
the S-shaped thing, which is there will be a distinct
advantage in terms of cost per malaria averted, the benefit
of going from a coverage of 25% to 30% of the population
are going to be lower than the benefit of going, say, from
45% to 50%.
Because when you go from 45% to 50%, you're in the zone
where every extra bed net is really helping a huge deal.
So that is going to be relevant when
we do the cost benefit.
So that's the case for bed nets.
So now, if we were traditional economists, we would make a
traditional economic argument, which is to say, there is an
externality.
Whenever there is an externality, we want to try to
do use prices or taxes to align the private incentive
with the public incentive.
That's why, for example, we would like to have a
congestion charge in London, or we have a congestion charge
in London to make it expensive to drive your car in London,
in the center of London, because when you drive your
car in the center of London, that's a pain
for everybody else.
That could be one of the reasons why we have taxes on
cigarettes, that smokers impose an externality on the
rest of the people, here both because of secondhand smoking,
and because they get sick a lot.
So you would think that society has a right to impose
a tax on them to try and discourage them from smoking.
So by using prices and taxes is where you can try and align
the private incentive to the social benefit.
Yes?
AUDIENCE: Can you do community incentives, like you tell the
community if everyone uses their bed nets as bed nets,
you'll give the community a certain number of fishing nets
so that people will encourage or force other
people to use bed nets?
ESTHER DUFLO: Right.
So one way is the prices, but another way could be to have
community incentives.
Indonesia has a program where they are trying to give
community incentive so if, say 90% percent of the community
is immunized, and x percent to the community is in school,
then they get some amount of money to build a road, or an
irrigation project, or something like that.
AUDIENCE: I'm just curious.
How much is given in foreign aid to fight malaria?
ESTHER DUFLO: That's an excellent-- how much is given
in foreign aid to fight malaria.
It's an excellent question, the answer to which I don't
know off the top of my head, but it's findable.
AUDIENCE: Because I was going to ask if the cost of
providing a country with bed nets is significantly less
than the cost of giving [INAUDIBLE] money to fight
malaria, then I don't even see why it's as big of a
debate as it is.
Clearly, they should figure out what's the most effective
way to distribute the bed nets, make sure [INAUDIBLE].
But the option of not giving them just wouldn't make as
much sense, in terms of cost [INAUDIBLE].
ESTHER DUFLO: Oh, I see.
So providing bed nets would be part of the
budget of fighting malaria.
So your question is that, if we're already spending so much
money on medicine against malaria, we would really be
willing to spend a lot of money on bed nets.
You're exactly right.
And I don't think the debate is that we want to try and
save money on the bed nets.
I think the debate is always about what's the best way to
get the money out.
So this would argue, so the fact that the private
incentive to get your bed net is low, would argue for
subsidizing the bed net, but only if the private incentives
are not large enough that people are already not buying
your bed net.
So suppose, for example, that people hated being sick,
which, presumably, they do.
Then, they would get the bed net anyway.
You would not need to subsidize the bed net.
So there would not be an effect of the price, because
the demand would be very high at any price.
So the fact that there is an externality justifies
subsidizing, to the extent that the private incentives
are too small for people to want to get them themselves.
Another traditional economics argument would be the learning
argument that was made earlier, which is that trying
your bed net once might give you the experience of it, and
once you knew how it works, and you know how well it
protects your children, you might be more likely to get
the next one.
And then there is an argument that mixes the two, which is
another externality argument, which is, if try a bed net,
and I realize that it protects my children and it's really
not so unpleasant, then maybe my neighbors will also see my
bed net, and say, oh, isn't this cool.
We want also a bed net.
So there is an externality in my trying, potentially.
Yeah?
AUDIENCE: But if you were charged for bed nets and the
borrower that could, again, come in to have the bed nets
[INAUDIBLE]?
ESTHER DUFLO: Yes.
So eventually, since there are those contingent benefits,
someone who is very rational might feel, already more than
50% bed nets in this community.
I don't need to get the next one.
So the private incentives diminish as the coverage
increases, which makes it more necessary either to subsidize
it even more, or to tax people if they don't get a bed net.
So this is an argument that is made for immunization.
So in this country, immunization is compulsory for
a range of diseases.
Except if you really don't want to do it because you have
some religious or whatever reasons for not wanting to be
immunized, then you can say, sorry, I refuse the
immunization.
And people worry that as diseases such as polio, or
diphtheria, or pertussis, these types of diseases become
less frequent, people don't have the fear of getting those
diseases anymore, and they want to free ride on the rest
of the community.
And that's, of course, bad, because being 100% immunized
ensures that the disease goes away.
As soon as a few people are not immunized,
it could come back.
And so there is this tension between once almost everyone's
immunized, your private incentive to do
it are almost zero.
So you might need powerful inducement to get to do it.
So those are the traditional economic arguments.
These are your traditional public finance--
let's use the prices.
That indicates that we should subsidize the bed nets.
And by the way, there is no reason to
stop at zero in principle.
We could pay people to use bed nets, for that matter, if this
was the way to get the optimal coverage in the community.
Yeah?
AUDIENCE: So one consideration that comes to mind is if
there's a segment of the population that is really,
really poor and cannot afford to pay any amount for the bed
nets, whether they're subsidized or not, those
people are also the least likely to be able to pay for
health care should they get malaria.
So they would have the greatest risk for everyone
else and for themselves.
So wouldn't you want to try to provide free bed nets for that
set of people, no matter what?
ESTHER DUFLO: Right, so that's another consideration that you
might want to include, a redistribution consideration,
which you might feel that people who are particularly
poor might have a very high private evaluation of the bed
nets, but might be credit constrained and not be able to
get the bed net.
And those are the same people who will also not be able to
cure themselves of malaria.
So here, that gives you another argument for
subsidizing bed nets, which is not an argument in terms of
disease eradication, but an argument in terms of
redistribution between people.
So those are traditional arguments.
They are taken, say, by Jeff Sachs, or by the WHO, and say,
we should subsidize bed net to a large extent, or
potentially, up to giving them away for free.
And then we have the less conventional economics, which
we discussed, which has the argument that goes in the
opposite direction, or the psychological sunk cost
effect, which is, you have to pay for something to really
appreciate its value.
There is a selection effect which is, if you give things
away for free, even people who don't want it or who don't
want it for its legitimate use are going to come and get it.
They're going to waste a lot of bed nets.
And finally, the entitlement effect, which counters the
learning effect, which is, once you get something for
free, then you expect to get it for free in the future.
And it might even have contingent things, which is
you're not going to want to get chlorine to purify your
water, unless someone is giving it to you.
You're not going to want to send your kids to school
unless they get a school meal, other things like that, which
find that you become dependent.
Yeah?
AUDIENCE: I have a question.
Couldn't you argue that it's not sustainable, [INAUDIBLE]
long-term policy and exit strategies, because if you're
[INAUDIBLE]
subsidizing and giving away bed nets, you might crowd out
the private sector.
And you won't [INAUDIBLE] your desired outcome, which is for
people to be using bed nets.
ESTHER DUFLO: So in the traditional public finance
argument, why would you ever want to stop to
subsidize the bed net?
AUDIENCE: Want to not subsidize--
ESTHER DUFLO: Yeah.
Why would you ever want to stop, given those arguments?
AUDIENCE: To create a market?
ESTHER DUFLO: Why would you?
Take, for example, immunization in the US.
Immunization is subsidized and compulsory.
Is there any plan to make immunization not subsidized or
compulsory?
AUDIENCE: That's true.
ESTHER DUFLO: There's no such plan.
This kind of argument would tell you that you want to
subsidize forever, because the private gains and the social
gains are not aligned for a fundamental reason, which is
my being protected by a bed net protects you as well, and
that's never going to change.
So in that sense, you're not doing a policy
for the short run.
You're doing this policy for the long run.
Now, again, we had this discussion earlier, which is
the questions of who provides the bed net, whether they can
be provided locally instead of imported, are all very
legitimate questions, but in a sense, unrelated to the price
you're going to charge.
So that's an excellent question, because it comes
back all the time, which is to say, oh, but
don't we want to exit?
Just think, whenever you want to ask yourself this question
about sustainability, ask yourself, why
would I want to exit?
Maybe I don't.
Maybe it is actually socially efficient to subsidize
something for eternity, because as Ben was saying, you
save on the cost of curing people from malaria.
So the argument that goes against giving people for free
are these arguments that giving bed nets for free or
even subsidizing them is counterproductive, in terms of
distributing bed nets.
It's counterproductive because of the sunk cost effect,
because of the selection effect, or because this
entitlement effect that then nobody is ever going to want
to buy anything, either a bed net or something else.
And these elements are very reasonable.
Both sides of the arguments are, in principle, very
reasonable.
And they might apply here.
We just don't know.
It's a very heated policy debate.
The laws that are involved in bed nets are nowhere near the
laws that are involved in oil or anything, but it's still a
fair amount of dollars, so people like those.
So there is a lot of debate.
So Jeff Sachs of the WHO relies on the convention
economics argument to say you should give the
bed nets for free.
Then you have people like Bill Easterly or Dambisa Moyo, who
are making the argument based on this entitlement effect,
sunk cost effect, the development of market, to say
we shouldn't give them for free.
And both arguments tell you, in a sense, we know the
economics, and the answer is obvious.
There is no reason to find out.
And I think there is value in both type of arguments that
they are making.
But there is no value in this last one.
Because since there is value in both arguments, we don't
know the answer.
The answer depends on the balance of how they turn out
in the specific application of bed nets.
So the true question we want to ask is the extent to which
we should subsidize bed nets.
And for that, what do we need to know?
Well, first we need to know whether or not bed nets are
really price elastic.
So are we losing a lot of coverage in terms of people
acquiring bed nets, if we start selling them instead of
giving them for free.
Second question we need to ask is the
immediate effect on use.
So is it the case that people who pay for bed nets are more
likely to use it than people who got it for free?
Third question is the longer-term effect.
Will it wreck markets?
And for that, that's the entitlement effect.
For people who get it for free, in the future, are they
more or less likely to buy one?
And for people who are around them in the community--
this is something we didn't discuss much, but if I'm
around you in the community, and I see you having a free
bed net, it could affect me in one of two ways.
I could say, first of all, oh, she has a bed net.
That's really nice.
Her kids are doing well.
I'm going to get one too.
I could say, oh, she got a free bed net.
Let me wait until I get--
I was going to buy a bed net, but now I'm going to wait
until I get a free bed net.
And so I wasn't going to sell a bed net, and now I'm going
to have give it for free.
So that's wasted money.
So again, we don't know which way it cuts.
We have to look in practice.
And those questions are pretty well-defined questions.
They are empirical questions we could principally
bring an answer to.
There are a lot of anecdotes.
They are this one, which is bed nets used as fishing nets.
That's a picture that was in the Malaria Journal, so it's
all peer reviewed and all that.
So this is the Easterly Dambisa Moyo argument, that
you are going to see the used as a fishing net, or wedding
veils, or what have you.
And then this is the other argument, of the other
anecdote of the bed net being nicely hanged in the room, and
the child, the healthy child who slept in there
under the bed net.
So that's not too helpful.
So we want to go further that the anecdote.
There are many anecdotes, and they cut both ways.
How do we go further than the anecdote?
So the first thing we could do-- so suppose you
were given this job.
I tell you, find out for me whether people who get their
bed nets for free are more likely to use it as fishing
nets or more likely to use them as bed nets.
And also, find out whether if I distribute the bed nets for
free, I distribute many more of them or I distribute the
same amount.
What would your first response to what you
should go out and do?
AUDIENCE: Yeah?
I would find two similar communities, and then
[INAUDIBLE]
give bed nets would be one, and maybe help someone start a
small business of selling bed nets in the other.
ESTHER DUFLO: So you would take two similar communities,
and in once case, give bed nets for free, and in one
case, start to sell them, maybe by finding a small
business, or maybe importing them to the village.
What would be an even---
we'll go back to that.
What would be an even easier, even more immediate way to do
it that we could think of to start with, if we needed to do
this quickly?
Yes?
AUDIENCE: Just look at the
communities where it is already.
ESTHER DUFLO: Right.
You would look at a community where this is already in
place, and you would say, well, in this community, the
bed nets are given for free, and in this community, the bed
nets are sold.
Let me try my thing.
Yeah.
In this community, the bed nets are given for free.
In this community, the bed nets are sold.
First question, do I see more bed nets where the bed nets
are not given for free?
Second question, do I see the bed nets more likely to be
used as fishing nets in those communities?
So that's, I think, what most people would--
that would be your initial instinct.
The problem you would have if you did that, as opposed to--
sorry, can you remind of your name?
AUDIENCE: [? Sif. ?]
ESTHER DUFLO: [? Sif. ?]
The problem to do that, as opposed to do what [? Sif ?]
suggested, is to know why some community happened to be the
one that got them for free and some community happened not to
have the free distribution.
So let's think of one reason why there might be a free--
if you were to start a free bed net distribution program
somewhere, where would you start it?
You have a country and you want to start a free bed net
distribution, what would you pick?
Yes?
AUDIENCE: If there was a particularly bad
increase, or something.
ESTHER DUFLO: Right.
You would try to pick a place where there is a lot of
malaria, presumably, or maybe a place where
people are very poor.
So let's work with the example where you would pick, to start
your free bed net distribution, the region where
there is a lot of malaria.
It would make sense.
So if that's the case that free bed nets are distributed
where malaria is a huge problem, then in these places,
even if they had to pay for the bed net, they might have
purchased them more willingly than in places where malaria
is not such a big problem anyway.
Because the private benefits of having a bed net is higher
in those [INAUDIBLE].
So this is what we call the counter-factual, which is what
would have happened in the place where the bed net got
distributed for free if they had actually been sold.
So let's look at it in the form of a simple graph.
So suppose we have two--
we are going to do the argument for purchase, and the
same kind of discussion we could have for use.
So suppose we have two regions, a high-malaria region
and a low-malaria region.
And suppose that God told us this is how many people would
buy a bed net, the fraction of people who would buy a bed net
in the high-malaria region and the low-malaria region, if the
bed net was not subsidized.
And this dot is higher, because since malaria is more
of a problems, people are more willing to buy bed nets.
OK?
So that's what we would have if bed nets were expensive.
And if bed nets were free, we would have those ones.
So compared to the previous dots, they are higher.
Why are they higher in both regions?
AUDIENCE: It's because they're free.
ESTHER DUFLO: Because they're free, so you're more likely to
get something free than to have to pay for it.
But they are still higher in the high-malaria region,
because why would you get a bed net in a region where
malaria is not a problem?
You really don't need it.
If you don't have a fishing boat, you don't need a fishing
net either.
So they are still higher in a high-malaria region then in a
low-malaria region when bed nets are free.
So this is what God would have given you.
But sadly, God didn't give you that.
God gave you either this point or that point.
What you observe is the purchase of bed nets in the
area where they are given for free, and the purchase of bed
nets in the area where they are expensive.
And those regions are different because one is a
high-malaria region and one is a low-malaria region.
So what you observe is the demand for bed nets when they
are free in a high-malaria region, and the demand for bed
nets when they're expense in the low-malaria region.
And what you don't see is those guys.
What you see is this and this.
What is the true effect of price on purchase in the
high-malaria region?
Where do I find it on the graph?
That's the vertical thing.
That's the true effect of free versus expensive in the
high-malaria region.
And this is the true effect of free versus expensive in the
low-malaria region.
So this is the true effect.
That's what I'm looking for.
Sadly, I don't have this, and I don't have this.
I'm not in very good shape.
What I do have is this and this.
So if I just did to comparison that we started with, we would
compare the high-malaria region purchase when it's free
to the low-malaria purchase region when it's expensive.
Take the difference.
That would be our effect.
So is that the true effect?
Is it biased upwards, or is it biased downwards?
Is that too big, too small, or the right size?
AUDIENCE: Too big.
ESTHER DUFLO: Too big.
And we can see it here, which we can re-put.
We can say, well, suppose we had what God would have given
all the numbers.
In the low-malaria region, this is the effect of price
and purchase.
And the rest is the best.
In the high-malaria region, this is the true effect of
price and purchase, and the rest is the bias.
So if we knew this and this, we could calculate the effect,
and we calculate the bias that we would get if we compare
this to this.
But suddenly, we don't have those.
So what this is saying, in other words, is that when we
compare purchase when it's free to purchase when it's
expensive, in the high- and low-malaria region, we combine
two effects.
We combine the effect that even at the same price, the
purchase would have been different.
So the counter-factual would have been different--
those are this versus this, and this versus this--
and the fact that there is actually an effect.
So that's why it's not a very good answer for the question
we're asking.
This we did for only two points, but we would have the
same thing if we had many price points.
So suppose this is the observed
demand at various prices--
when it's free, when it's 10 shilling, when it's 20
shilling, when it's 30 shilling.
That's the observed demand.
So someone could say, well, I'm going to trace a line
here, and that's going to give you my elasticity of purchase
with respect to the price of the good.
Now, let's say if God had given us the observed demand,
the demand we would observe in the region with the free bed
net if the bed net were not free, that's the demand we
would observe in this highest-malaria region.
It also decreases with price, but less
than we see in reality.
And why does it decrease less than we see in the data, the
yellow dots?
So the yellow dots are what we would see in
the high-price region--
so in the free region, what we would see in the zero price
region, if the price were in fact 10, 20, 30, 40.
So why is it flatter than the observed curve?
Yes?
AUDIENCE: Because it was free, [INAUDIBLE].
ESTHER DUFLO: So this is what is free?
This is a bit more.
This is the demand when it's free.
It's very high.
This is in the next region, where it costs 10 shilling.
It's a bit lower.
This point is telling us, this is how many bed nets the
people in this region would purchase if the price was, in
fact, 10 shilling instead of being free.
So this and this and this, we don't observe.
But we just say, let's say I'm telling you this is God told
you what it would be.
The reason why it is higher is because the region where it is
free is a region where people need the malaria nets a lot.
So even if they had pay 10 shilling, they
would still buy them.
And even if they had pay 20 shilling, they
would still buy them.
And even if they had to pay 30 shilling, they would still buy
them, although less, because of course they are sensitive
to the price.
But the difference between the yellow point and the red point
is the yellow point is just the effect of the price,
whereas the red point also has the effect of the fact that
you're more likely to have to pay for bed nets in places
where the malaria is not such a big problem.
So the red dot, which is what we observe in reality,
combines the effect of the price and the fact that the
regions where people have to pay are different.
Yeah, Ben?
AUDIENCE: The x-axis is price?
ESTHER DUFLO: The x-axis is price.
Yeah, sorry.
I should have--
it's like this, 0, 10, 20, 30.
AUDIENCE: It's still not obvious to me why if it's
free, if you go from zero to, let's say, a million, why the
demand for free bed nets would change [INAUDIBLE]?
ESTHER DUFLO: No, it's not the demand for free bed nets.
This is always going to be the demand at this price--
0, 10, 20.
So it's still declining, you see?
AUDIENCE: No, I'm saying for free bed nets.
ESTHER DUFLO: Oh.
For free, it's pretty high.
AUDIENCE: Why does it change at all, if you go
from price 0 to 30--
ESTHER DUFLO: Oh, you're wondering about this one.
You're wondering about this point.
You're wondering, in the low-malaria region, if I give
you a bed net for free, why don't you get it?
AUDIENCE: Well, no.
Because the x-axis is high instances of malaria, low
instances of malaria.
ESTHER DUFLO: Yeah.
AUDIENCE: You switched the price.
I'm confused why changing how much a free bed nets costs
would decrease the amount of purchases for free bed nets.
ESTHER DUFLO: So what is a little tricky is that there
are two things in the axis.
There is the fact that this is a high-malaria region, and the
fact that it's a low-malaria region.
And it turns out-- but this is what is very important--
it turns out that the price is related to the
incidence of malaria.
So here, for example, in the two-region case, I have given
the bed net for free in the region where
the malaria was high.
And the reason is because if I'm a good policy maker and I
don't have that much money, that's what I will do.
I will first give the bed net for free in the region where
malaria is high.
And I will ask people to pay for the bed net in the region
where malaria is low.
So what I observe in reality is the demand for free bed
nets in the high-malaria region and the demand for
expensive bed nets in the low-malaria region.
So if I compare the difference between the two,
and if I call this--
I'm combining two effects.
I'm combining the effect of the price, which is, given the
same region, people are more likely to get a bed net for
free than to pay for it, and the fact that people, given
that bed nets are more useful in a region where there is a
lot of malaria than in a region where
there is little malaria.
People are more likely to get bed nets at any price--
the red dots are for the same price--
at any price, people will be more likely to get bed nets in
the high-malaria region than in the low-malaria region.
So if you compare within a line the yellow to the red
dot, you get the effect of the price.
If you compare across columns within the same color, you get
the effect of being in high- versus low-malaria region.
And you see they tend to go in the same direction, which is
what creates your bias.
All right, do you get the
two-region, two-prices example?
If you get the two-region, two-prices example, then this
one is the same, but with four prices.
Now we have four regions--
a region where we give them for free, a region where we
give them for 10 shilling, a region where we give them for
20 shilling, a region where we give them for 30 shilling.
And this is what I observe in reality, a very steep slope.
At 30, almost no one buys it.
But this is due, again, to two things.
One is that that's expensive.
So even if malaria was a real problem, people would be less
likely to buy them for 30.
And, in addition, those regions where people had to
pay a lot of money for malaria is precisely because malaria
is not such a big problem in those regions.
So in order to decompose those two effects, what I'm doing is
that I'm playing God and I'm telling you, this is what the
demand at various prices would have been in this first
region, in the zero region, in the high-malaria region.
So this I don't see in reality.
In the world, I don't see that, but this is what it
would have been.
And it's a little flatter than this one because
this is like the bias.
This is saying, these are places which don't really need
malaria, and this is the effect of prices.
The yellow one is a true effect of prices, and the
vertical lines are the bias that are added by the fact
that prices are expensive in places where a bed net is not
very useful because malaria is not so much of a problem.
Yeah?
AUDIENCE: I have a question.
Why is there not a bias based on your environment and how
much malaria there is when they're for free?
ESTHER DUFLO: Well, when they're for free, we observe
the true demand at free.
So that happens to be the same point, which is, I'm giving
you what I observe.
And the free region is the demand when it's free.
What I would like to know, then, is what would the demand
in the free region be if, in fact, it had been 10 shilling?
So this is this counter-factual, which is,
there is something we don't observe, which is precisely
what we need to compare to the region where,
in fact, it is free.
Ask as many questions as you have.
The more questions, the better.
Yeah?
AUDIENCE: I was wondering why [INAUDIBLE]
more likely to go from zero to 10 shillings.
Do you see that the [INAUDIBLE] decrease in the
[INAUDIBLE]
ESTHER DUFLO: So you have-- so what is your name?
AUDIENCE: Katja.
ESTHER DUFLO: Again?
AUDIENCE: Katja.
ESTHER DUFLO: Katja.
Katja has a question, which is, she doesn't believe that
the elasticity is the way I drew it.
You think that it's more like steep and then flatter?
AUDIENCE: Yeah.
ESTHER DUFLO: Possibly.
That's the way I made that up.
I consider that zero and 10 is kind of similar, but that has
no reason to be true.
And substantially, you're absolutely right.
It could be that, in fact, there is a big drop in demand.
But then the red point would probably be even lower.
Yeah?
AUDIENCE: Why were the experiments conducted so that
you only get the orange data points?
Why did you not mix up different communities that
have had malaria and [INAUDIBLE] malaria
[? for each-- ?]
ESTHER DUFLO: That's an excellent point.
So this is not supposed to have come from an experiment.
This is the real world.
[INAUDIBLE]
a real world outside of an experiment.
And outside of an experiment in the real
world, it is likely--
it doesn't have to be the case, but it's likely that
policy maker will make the bed net available for free in
high-malaria region, because it makes sense for them.
But your question exactly brings to what the answer to
the problem is.
So we have a problem, which is that we observe the low prices
in places where the need is high, and high prices in the
regions where they need is low, so that
leads to this bias.
And the solution is exactly what you suggested, which is,
let's have variation in prices in regions where
the need is the same.
Yes?
AUDIENCE: So on the x-axis, are you exactly correlating
the price of the bed nets with the incidence of malaria, or--
ESTHER DUFLO: So what I'm assuming, I'm telling you this
doesn't have to be true.
And the problem is we'll never know, because we won't observe
both in the real world.
But I'm telling you this happens to be like that in
this particular fictional world that I constructed,
where this was like that.
AUDIENCE: But if you go along the x-axis to the right, you
mean that bed nets get more expensive and malaria
incidence goes up?
ESTHER DUFLO: Goes down.
AUDIENCE: I'm sorry, goes down?
ESTHER DUFLO: Exactly.
AUDIENCE: OK.
ESTHER DUFLO: I constructed it that way.
You could construct the opposite example, and you
could make up a story where the richer regions have more
political power, and they also have less malaria.
So the richer region will get the free bed nets, and they
will also have less malaria.
In that case, where would the observed compared to the true
elasticity, where would the red dot be, if, in fact, the
correlation was the other way?
AUDIENCE: They would go the other way?
ESTHER DUFLO: They would go the other way.
So the red dot would be above, because the bed nets are more
expensive where they are more needed.
And your question brings in an essential question, which is,
sadly, we can't know.
We can know some stuff, which is we can, for example,
measure malaria prevalence.
But we never observe the counter-factual.
So either we observe the demand, where the price is
high, in the places where it's high, or we observe the demand
where the price is low in the places where it's low.
And we never get to see the demand where the price is low
in the places where it's high.
That's the missing data point.
That's why this is what we are missing.
In other words, we don't see those yellow points.
We don't see what the demand would have been in a zero
price region if the price, in fact, had been 10, 20, 30.
We just don't know.
So the solution is what you suggested, which is to say,
why don't we take one region and try to vary the prices in
those regions?
Or in fact, we could take two regions, a high-malaria region
and a low-malaria region, and vary the prices
in those two regions.
And this is where the word experiment comes up.
This is where the experiment is, which is the way you would
do it to be completely sure that there is no difference
between the places or the people which got the bed net
for free, and the places or people which had to pay for
it, is you would randomly assign the price of the bed
net to different regions or two different people.
So this is what is done, for example, in medicine when you
want when you want to find out the
effectiveness of a new drug.
You don't give the new drug to people who need it the most.
Otherwise, you would find that the drug
killed a lot of people.
You take some part of people who need the drug, and you
randomly assign some people to take the drug and some people
to get the placebo.
You might also take a sample of people who need the drug
less, and randomly assign the drug within them, to find out
side effect if you misprescribe.
But you wouldn't give the drug to people who need it, and not
the drug to people who don't need it, otherwise all of the
drugs would be sure to kill a lot of people.
So most evaluation of social policy is trying to estimate
the effect of policies by doing these kind of
comparisons, this point to this point.
And that creates this bias situation.
And in fact, you can try and make more progress on this
question by creating experiments where you fix the
region, or you fix the environment, and you randomly
assign the prices.
The randomization ensures that there is nothing
systematically different between the people who got the
free bed net and people who didn't get it.
In other words, there is no--
if we go back to this graph, for example, the places that
got the free bed net and the places that had to pay for the
bed net, if they had gotten it for free, they would be at the
same level.
And if they had pay for it, they would
be at the same level.
There is now no difference between the region who paid
for the net and the region who didn't pay for the net.
One point before going into the results of what Cohen, and
then Pascaline Dupas found for the bed net is that of course,
this is not true if it's just one village and another
village, like Steve suggested.
Why is it, if we took only one village, and in one case we
make free, one case we make not free-- we can flip a coin,
and then we compare--
why is that problematic?
Two villages--
why is two villages not enough?
AUDIENCE: Because you can't make sure that everything is
the same [INAUDIBLE]
like one village might have more [INAUDIBLE]
actually care about each other, or one village might
end up having a really rainy season, so all the mosquitoes
happen to swamp around it.
ESTHER DUFLO: Exactly.
Two villages, even if there is nothing systematically
different, because you've thrown a coin, so you didn't
choose one village rather than the other for their
characteristic to give the bed net for free or to ask people
to pay for them.
Even in that case, there are things that are different
across villages that you can't fully control.
So you need the samples to be large enough such that all the
other differences between people or between regions
average out, so that even though you do not observe what
the demand for bed net would have been in the free region
when actually you ask people to pay for it, you would not
observe that.
But you can be confident that what the demand you observe in
the other region where it was free gives you the right
counter-factual.
And for that, the sample needs to be large enough so that all
the noise and the idiosyncrasies get swamped.
So let's look at two sets of experiments.
Both were Pascaline Dupas, who is a professor at UCLA, was is
involved in both of them.
The first one was conducted with Jessica Cohen.
In and around this place, which is
called Busia in Kenya.
This hotel, you can see that the beginning of the hotel is
called "Blue York," where I spent a lot of time.
And so what did they do?
They randomly chose clinics, prenatal clinics, they gave
them nets to give to people who come for their prenatal
exam, either at zero or 20 shilling or 30
shilling or 40 shilling.
So the unit of randomization is the clinic.
And then they compare how many bed nets they sold, and
whether the bed net got used, and therefore the effective
coverage in those clinics.
And this is what they find.
So the little vertical line here is
the confidence interval.
So it's taking into account all the noise that
exists in the data.
And so what is the conclusion from this graph, at free, 10
shilling, 20 shilling, 40 shilling?
This is the number of nets sold per week, I think.
AUDIENCE: Does that indicate if the customers actually use
the bed net?
ESTHER DUFLO: No.
So far, this is the first look at, which is just how many bed
nets were given out.
Yeah?
AUDIENCE: [INAUDIBLE]
the demand curves downward.
ESTHER DUFLO: The demand curves downward, and it's
quite steep, right?
Basically, at 40 shilling, which is still heavily
subsidized, because the full price of a bed net is more
like 80 shilling, you distribute only about 10 bed
nets per week, versus 40 per week, when you
give them for free.
So it goes down quite steeply.
And I remember, because they were randomly selected, we
know that it is due to the price, and not due to
differences across those regions.
Yeah?
AUDIENCE: Yeah.
That's funny, because the error bars are pretty big.
Like, if you if you looked at the lower error, versus the
higher error, it's [INAUDIBLE].
ESTHER DUFLO: So you take this one compared to this one.
That's the confidence interval.
So we are 95% confident that the truth is somewhere in
between there.
That the 95 confidence interval, [INAUDIBLE].
Right?
So you can know that this is systematically
different from this.
You're right that this and this, the
confidence interval overlaps.
And in fact, the numbers are quite similar.
This is why I don't answer someone who was asking why
didn't I draw the elasticity that way I'd drawn it that
way, because I already knew the answer to the question.
I was ahead of the game, slightly.
So zero to 10 is not such a big difference.
Maybe 10 is not that expensive.
But 40 is definitely different from free.
You're right.
Certainly we would like those bars to be smaller.
If we had more observations, they would be.
They would be even more precise.
Yes?
AUDIENCE: Were the clinics far apart from each other?
It could be, say, I'd go to the clinic where I'd have to
pay 20 shillings [INAUDIBLE]
ESTHER DUFLO: Right.
That's a very good point.
The people shift from one clinic to the other.
So they couldn't really do that, because the clinics were
quite far away.
On the other hand, what they did find is a lot more people
coming to the clinic, presumably to get the bed net,
which is a good thing, because it cost subsidizes other
services that you get in the clinic, in
particular a test for HIV.
And if the mother is HIV positive, then you can give
them Nevirapine just before the delivery to prevent the
transmission to the [INAUDIBLE].
So that's another story, which is a reason why you might want
to distribute bed nets if people like them.
Now, this was your question, which is, but are people are
using them?
And so far, the usage, you can ask people what they tell you.
But they could lie.
Or you can try and go to their home and see whether you see
the bed net.
And here, what's the conclusion?
So this is conditional, having gotten a bed net.
So what they did that they took the register.
They saw who got a bed net, and they went to their home
and said, what are you doing with the bed net?
Is it a fishing net or are you using it for a bed net?
And what do they find?
AUDIENCE: What's the y-axis?
ESTHER DUFLO: So it's percentage divided by 10.
So it's 0%, 20%, 40%, 60%, 80%, 100%.
Ben?
AUDIENCE: I'm a little confused about the why.
So 10 is interesting to me, like why 50% of the people who
purchase the bed nets actually use the bed nets.
ESTHER DUFLO: So a bit more, it's more like 60%.
AUDIENCE: For 10?
ESTHER DUFLO: Yeah, for 10 shilling.
It's about 60%.
AUDIENCE: Can you help me understand
why that trend happens?
ESTHER DUFLO: Oh, why is it going down?
AUDIENCE: Right.
ESTHER DUFLO: It's not--
I mean, going back to the question earlier, it's not
significantly different.
So it's kind of all similar.
So overall, about the trend, what do you have to say?
This is pretty similar.
It seems pretty flat.
So there is no very big evidence that how much of paid
for a bed net influenced whether or not you're going to
use it or not.
And it's not 100%.
It's more like towards 60% to 70%, so not everybody
uses the bed net.
But how much they pay for it doesn't affect whether or not
they use it or not.
Interestingly, when they went back six months to a year
later, more people are likely to use them.
So some people just took them because they were free, maybe,
or they were not very expensive, and decided to
store them for future usage, which is also
something you can do.
So people do not seem to not use the bed net because they
got them for free.
And the result is that if you look at the effective
coverage, the effective coverage is very strongly
declining with price.
So the conclusion from their study is that you should give
the bed nets for free, because you get many more bed nets
out, you're much more likely to go--
if you get them for free, you're going to
be above 60% coverage.
And once you go above 60% coverage, you're more likely
to buy them.
But before you go, I want to give you the
epilogue, which is--
so this is the reading I asked you to see, which is people--
so this got posted on Daniel Roderick's blog, under the
title "Jeff Sachs Vindicated," which is to say, oh, yeah, we
should give bed nets for free.
This experiment showed that.
And then people complained, and said, this is only
pregnant women, and pregnant women all need the bed net, so
they are going to use it at any price.
The sunk cost effect won't be there for pregnant women.
And secondly, it's Kenya, where bed nets are still quite
well-known.
So what are people objecting?
People are objecting to saying, the experiment gives
you a lot of internal validity.
We know now that in the specific context of clinics in
western Kenya with pregnant mothers, there is no effect of
the price you pay on whether you use.
But maybe this doesn't apply to Uganda, Maybe it doesn't
affect non-pregnant women, et cetera, et cetera.
So this is a question of external validity.
So what's the solution?
When these kind of questions are raised, what's the
solution to make progress?
You've can't ignore these questions.
They are very good questions.
What's the solution to make progress?
Yes?
AUDIENCE: Try it in other areas.
ESTHER DUFLO: You want to try it in other areas.
So in fact, in bed nets, this got done.
So this got tried first in different countries, so in
Uganda, in Madagascar.
And secondly, it got tried in Kenya, but as I was going to
say, real people, not pregnant women, but people from the
market, men and women.
And here, vouchers got given at various prices to
individuals for them to pick them up in the shop.
So now this is an environment where have you would have
expected to be more likely to find a sunk cost effect.
Moreover, the experiment was also done to look at these
longer-term consequences.
So after six months, they went back again to the same people,
and tried to sell them a bed net for 100 shillings, so not
the lowest price, and not the highest price.
And so the question is, the people who got the first bed
net for free, are they more likely to buy the second one
for 100 shilling, or are they less likely to buy the second
one for 100 shilling?
So I'll run you to the result quickly.
So they find the same effect of price on purchase, that the
more you pay, the less you get, quite steeply.
They find the same lack of effect of price
on whether you use.
And so this is not pregnant woman anymore.
So this kind of generalizes a bit the result.
And this is the effect on future approaches, the
confidence bar, a little bit high.
But if anything, what you find is that people are more likely
to buy a second bed net when they got it for free or almost
free than when they were offered the
option to pay for one.
And this is despite the fact that at that time, they
already had a bed net.
So presumably, their need for a second bed net is less so.
So it seems that the learning effect dominates the
entitlement effect.
So if we go back to the wrecking market story,
sustainability question you could say, well actually,
giving a sweep of bed nets for free might be a good way to
create a market.
Because you create a demand among people who start
learning and say, actually, it's kind of nice,
that bed nets idea.
The last way in which you create a demand is by creating
this first user of a bed net.
So this is the last card that I'm going to show you.
This is the purchase of a bed net if you have to pay for it
if none of your neighbors got it for free.
And this is a purchase of a bed net, if you had to pay for
it, if all of your neighbors got it for free.
And that is randomly assigned, because depending on who your
neighbors are, where they are located, what kind of voucher
they get, this is just random whether they get this one.
And what you see is that if your neighbor got bed nets for
free, you're more likely to get one.
So there is actually a positive social effect.
So the reason why I wanted detail into this experiment is
that that's an experiment that shows us how we can use
experiments not only to evaluate the impact of a
policy, but the answer those questions that help us
understand how people decide whether the entitlement effect
is bigger or smaller than the learning effect, whether the
sunk cost fallacy exists, whether how the big the price
elasticities are, et cetera.
And we need to design the experiment to
answer all those questions.
And then we can start informing the policy debate.
Sorry for running over.