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FRANK SCHILBACH: All right, I'm going to get started.
This is lecture 14 of 14.13 The lecture
today is about attention.
OK.
Good.
So where are we at in this class?
In this class, we talked a lot about preferences so far.
Think about preference describing in economics.
What do people want?
What makes them happy in one way or the other?
We talked about time preferences, risk preferences,
and social preferences, time preferences.
How do people make choices over time?
Risk preferences are, how do people
deal with risky situations when some things are uncertain
and others are more certain?
Or sometimes good things happen, sometimes not.
And there's a probability distribution over those events.
And how does that affect how you make choices?
And social preferences is what we
talked about during the last few weeks, which
is how does the presence of others affect our choices?
How much do we care about others?
And do we decide or make choices differently
if others are involved?
So now what we've done with preferences
is sometimes saying we have our models
to think of ways to think about what makes people happy.
The second part when you try to make decisions
is when you look at your environment, what are prices
like?
What do we know about others?
What are our beliefs?
And what do we attend to?
And how do we learn when we get new information?
So what information do we have?
And what information do we attend to?
And how do we learn when we get new information given to us?
And so we're going to talk first about attention
in this lecture.
And then the next couple of times, we're
going to talk about beliefs and learning.
So what we're going to do today is
we're going to talk about three broad issues.
One is going to provide you some motivating evidence
about attention.
We had a little bit on this in lectures 1 and 2.
But I wanted to remind you of that a little bit.
Then we're going to talk about two specific papers.
One is a pretty famous paper by Raj Chetty
and co-authors on inattention to taxes.
And then you're going to talk about a second paper, which
is learning by noticing.
In particular, we're going to ask the question of,
how is it possible that people do not attend to things that
are important in their lives?
You might say, well, if attention is limited,
that's all good.
But then we should expect that people attend
to really important stuff.
So some sort of rational inattention models
would say, well, it might well be that people
are inattentive in some ways.
But really, it can't be possibly that the welfare
losses from inattention are large
because if they were large, if there's things
that people missed, then they would
pay attention to those things and shift their attention
optimally.
The learning by noticing paper is
one theory, at least potentially,
that addresses this question.
The way these movie perception tests work is, essentially,
they look for what's called change blindness.
So the way this works is, often, there's
one actor, which is this guy here.
I think you can see probably right now there's
some guy who does some activity.
You're supposed to watch the guy.
And then there's a second scene in some ways where
the person does something else.
In this case, the guy--
sorry, where is he?
The guy is taking a phone call.
And so what happens then is--
essentially, then, this guy that you see here
that takes a phone call is a different person altogether.
And so that's called change blindness
where, essentially, people then tend
to not notice at all that there's two
different people in a scene.
There's other types of experiments
that do this, as well.
One version of that would be people who go to a bank.
There's a bank teller.
And this is like all psych experiments.
There's a bank teller.
Here's the other guy.
So you see this guy.
He looks actually very different to the other guy
that you had seen before.
So people go to the bank.
There's a bank teller.
The bank teller says, oh, yeah, I'll
have to just get something from the back.
And then another person shows up who's
a totally different person, often looks very different,
sometimes wears different things.
And people just don't notice at all.
And that's sort of type of experiment
is called change blindness.
I've already shown you the gorilla test before.
I'm going to not play it again because I've already seen it.
But essentially, it's the same where
people are asked to pay attention
to how many passes people play in a basketball game.
And then there's a guy who's in a gorilla
suit who shows up and walks through the whole screen.
And many people just miss the gorilla suit.
Now, what's going on here?
There is a large number of these types of experiments.
They're called change blindness or inattention experiments.
And there's another version of that,
which is called the dichotic listening experiment.
This is going back to broadband, 1958.
They essentially look something like this
where there's people who wear headphones with messages.
On the one hand, on our left, there's
supposed to be ignored inputs.
And on the other hand, there's supposed to be attended inputs.
So the person in the experiment is
asked, only listen to stuff that's, I guess,
in your left ear.
These are the attended inputs.
I'm going to ask you some questions about that.
And then what you're supposed to then do is--
are you still stuck?
This is bad.
One second.
I'm going to unshare my screen.
Exactly.
Give me a second.
So the way this works is you would have headphones on.
And on one hand, you hear inputs that you're
supposed to attend to.
On the other ear, you hear inputs
that you're not supposed to attend to.
And usually, then, you get explicit instructions
to attend to the message in one ear
and then asked later about message in the other ear.
People can't remember it.
And then what these experiments often are--
when asked to keep a number in their head,
people remember the played message much less.
So essentially, what this shows is that, A, I guess,
people are pretty good at shifting attention in some way.
But attention is limited to the extent
of when you're also supposed to attend to something
else at the same time.
It's essentially too much going on,
and it's really hard for you to remember everything.
And so to some degree, it tells us, A, I guess,
attention is limited.
We tend to focus--
when instructed, at least, we tend
to focus on stuff that's important, right?
So like in the broadband experiment,
if I tell you listen to the stuff in the right ear,
you actually focus your attention
to the stuff in the right ear.
You miss the stuff on the left ear,
so you can sort of direct your attention to stuff
that you think is important or you've
been instructed to focus on.
So that kind of works.
But at the same time, attention is limited in the sense of you
can actually not remember what's in the other ear
because you didn't attend to it.
So in some sense, it's not like you automatically
remember stuff.
You have to pay attention to things.
And then at the same time, when we now exogenously reduce
people's attention by telling people
to keep a number in their head, distracting them in some way,
people are much more--
even playing the played message, the message that you're
supposed to remember.
I'm sure they don't remember the other message, either.
OK.
So then in addition, which I already alluded to,
attention is limited.
There might be different factors that might
affect people's attention.
So what factors might be important for attention?
Could be your physical environment in some ways.
It could be it's really hot.
It could be it's really cold.
It could be other threats in the room,
so if you're in some place where you're
worried that there will be wild animals coming anytime soon.
Physical environment could be really important.
It could be really loud.
Distractions could be social media.
It could be other stuff that you're just
trying to do at the same time.
Maybe you're trying to solve some problems right now.
Maybe you're trying to prepare for some-- for example,
I had a phone call just before our class.
And I was also trying to think about what to do in class,
and it's just really distracting to have
other things you're thinking about at the same time.
Could be worries about your own or others' well being.
It could be sleep or what people were saying already,
people's physical environment.
We're going to talk about some of this in the poverty lecture.
So there in particular, one thing
that poverty tends to come along with
is sort of a bunch of different ways of--
in addition to not having money and many other deprivations,
poverty tends to come along with lots of other factors
that might reduce people's attention.
And that's to do with sleep.
It's to do with exposure to noise.
It's coming with worries about people's health
and so on and so forth.
There's some question about practice.
Can you actually practice attention?
And there's some people who would
argue, at least in education, maybe at younger ages--
suppose you sit kids down and have
them practice focusing on tasks like multiplications
or whatever and do math problems.
Some of this, some people would argue,
in addition to just helping people
learn math, actually the numbers and so on and how to multiply,
you might also actually just help
students learn how to focus and how to pay attention carefully
to things and particularly sustained attention
and not get distracted by other things.
Other distractions, by the way, also,
like temptations, for example.
So if I put a delicious chocolate cake in front of you
and have you-- and if you're really hungry,
that might be actually really hard
to pay attention to whatever else
you're doing just because that's really distracting to you.
OK.
And so we're going to, for now, keep thinking
about attention being fixed.
We're going to get back to the issue of attention
being malleable and potentially being
depleted by issues such as poverty at the end in the very
last lecture.
But for now, we're going to look at--
think about attention as fixed but limited.
And now we're going to look at, what
are the consequences of that?
OK.
So then one question you might ask
is, well, this listening task that I just showed you
or when a monkey walks through some video or the like,
it's a pretty low-stakes situation.
Who really cares?
And one Chicago view of economics
would be to say, well, these are just low-stakes situations.
But once stakes are really high, then people
will surely pay attention.
And so there's a number of different papers
that look at this issue.
But one quite nice example here is from the stock market,
arguably an event of high economic importance
because people make a lot of money, potentially, from it.
So there's this very nice people by Huberman and Regev
from 2001 which has--
it's essentially an event study and a case study
of stock market development of a company called EntreMed.
And this company in 1997 on October, November
has very positive early results on a cure for cancer.
Now, for any of these types of companies,
having new cures and new medications or vaccines
or the like are hugely valuable because they can sell a lot
of their product in the future, which means, essentially,
positive news about that means you'll have lots--
at least with high probability or higher probability--
large profits in the future, to the extent
that the stock market is an indication of that.
You might expect the stock market to go up.
Now then, November 28, the journal Nature,
which was a very highly prominent scientific journal,
features this new very prominently.
And The New York Times, in fact, reports on it
on page A28, which is very much in the back of the paper.
And on May 3, this is a whole six months later.
The New York Times again features
essentially the same story as on November 28 on the front page.
OK.
Now, then on November 12, 1998, the Wall Street Journal front
page then reports about a failed replication.
It's essentially to say, well, these
are promising new early results.
These early results are often small samples.
And it's not quite clear, does it replicate really
with larger samples and so on.
Is this really a good cure?
And so you kind of won't have replications.
And really, only if you're able to replicate your results
is this actually something that's useful
and that you can make money off.
Now, what happened to the EntreMed stock prices?
And so the first question you might
say is, well, in a world of full attention
with unlimited arbitrage, as in if people
took full advantage of the news and reacted perfectly,
what would we expect?
And second, in reality, what did actually happen?
So let's first ask the first question about,
with full attention, what would we expect?
I guess there's a bit of a question what
happens in the first one.
There's a bit of a question, is there insider trading?
Or who gets the news in the first place?
So one thing you might say is, well, maybe the first one, only
the company knows.
And maybe that's not public knowledge.
And then if there's insider trading,
maybe the stock market might go up.
But surely, like in number two, if Nature prominently
features it, there's going to be a bunch of traders,
a bunch of people who invest in this company or not.
If they pay attention, they should really
know what's going on, and they should really--
the stock market should go up.
Conditional on that, on the November 28 news, on May 3,
there's really no news here, right?
It's kind of like we knew this before.
If everybody was paying attention before carefully,
the stock market should have incorporated.
The news is out.
Traders know.
You should buy this, or stocks at this company
is going to be more profitable.
So stocks should go up.
So really, if there's full attention,
you expect nothing to happen on May 3, '98.
And then if there's a failed replication, well,
to the extent that this means this cancer cure is entirely
useless, the stock market should essentially just go down
to where it was before.
Now, but what about in reality?
So let me actually just show you.
So here's the reality of this.
So there's not even--
there's the previous events done in here.
This is essentially the first story that comes out.
You see a little bit of an increase here.
But actually, quite a bit in relative terms with something
like 5%.
It seems like people just didn't really quite
notice what was going on.
And there's also no trend upwards.
It's not like the news is spreading across people and so
on.
And then there's like a huge jump now in The New York Times,
right?
So this is essentially here, it's in The New York Times
but in the back of the journal.
Up here, it's essentially The New York Times, the front page.
And suddenly, lots of people pay attention
to news that's actually not news because that was already
in The New York Times before.
To the extent that everybody pays attention
to this, unlimited attention and unlimited arbitrage,
we should essentially expect no effects whatsoever.
So we see a huge spike in the stock market price.
Maybe the stock market overreacted a bit
and went down a little bit.
But then what we see here is then the negative effective
of the failed replication.
Notice that here, the stock market is still quite a bit
high.
The price is still up quite a bit high, maybe twice as high,
about 20 compared to 10 as it was before.
It's a little bit hard to interpret that because it could
just be that maybe there's still a chance
that the cure might work out.
Maybe there's other news about the company in the meantime
that are positive and so on.
But the key part here is the fact
that the stock market went up here on May 4, 1998,
really is saying it's news for lots of people.
And really, it shouldn't be news.
And there shouldn't be any reaction
because, essentially, it's old news,
as you would say, in the sense of people in 1997
in November 28 already reported all of that.
Does that make sense?
OK.
And there's lots of examples of these kinds of things.
But essentially, some of this is--
in attention, some of it is also confusion.
I don't know if any of you have heard
of what happened to the Zoom stock market price,
stock price.
I don't know if any of you have heard of this story.
So essentially, there's a company Zoom,
which is the company that we're using
right now to record this video.
The stock market price of Zoom has
gone up a lot during the last three months,
rightly so because Zoom now has--
Zoom's profits has gone up a lot.
For example, MIT now has a corporate license
of Zoom, which essentially means thousands of people
now are using or can use Zoom, and that's an expensive thing
to do.
It turns out there's another company that's
also called Zoom except for that it's a different company
and has nothing to do with the actual Zoom technology.
It turns out that the Zoom stock market
price for this other company went up a lot, as well.
The ticker for that company is actually ZOOM, so like Zoom,
as opposed to the actual Zoom company
that we're using right now.
Their ticker is ZM.
And so at some point, actually, the trading
for that other company was halted, presumably
because people were very confused,
and they were not really paying close attention
to what is the right ticker, what's the right company
that they're actually buying.
They thought they were buying Zoom,
like the actual online video conferencing
company, while in fact they were just
buying some other company that's actually not
even doing anything anymore.
So there's lots of stories about people being inattentive
even in situations when stakes are really, really high.
Now, then, you might say, well, how do we now measure?
So now in some sense we have some evidence here
that people are-- in some sense somewhat informal evidence
that people are inattentive.
Now, how would you measure the impact of inattention overall?
So if you wanted to just measure and demonstrate
that people are inattentive, in addition to what I've just
shown you, what might you do?
How might you do that?
There's some information that you usually get in the world
and they should have.
One example that we can discuss is essentially prices or taxes.
And now if you want to demonstrate that people
are actually missing those prices or taxes, what
you can do is now you can make it very salient.
You make it really apparent to people.
And then you can look at, when you look at changes in prices
or the change of making things from non-selling to selling,
how do people react?
Or maybe you make, for example, taxes very salient.
What happens to people's demand for certain products?
And if then making things salient changes people's
behavior, that then identifies underlying inattention.
So if you just-- people don't have access
to certain information, in some sense, that's
less interesting because that just means,
well, I don't have the information
that's really available to me.
But in some ways, I could make information
that's really very salient--
I essentially could reduce the salience,
as you say, of certain types of information-- again,
information that should be available to them.
For example, suppose I do sales.
And I'm trying to, as a company, sell things.
You go to a store.
And usually, sales are made very salient to people.
Now you could essentially just change the prices
without making these sales very salient.
And then you could look at, how attentive are people to that?
In a way, that's, in some ways, less natural, right,
because when people are--
in a way, what we want to demonstrate
is that in people's real lives, there's
information available to them.
And they're not really paying sufficiently much attention
to it.
So if you can then change that in some ways
and demonstrate that now they're changing their behavior,
that must mean that previously, they
had been like misoptimizing.
If instead you did something like
if you reduce the salience of certain types of information,
that's, in a way, somewhat less interesting because it would
say, well, it doesn't really mean that they
were inattentive to start with.
It's more like you're hiding something from people,
and now they can't find it.
That's, in some ways, somewhat less interesting.
But I think in principle, you'd also, exactly as you say,
identify inattention.
So there's a few type of things that people have done.
And to be clear, there's often a pretty fine line
between attention and memory.
So one thing we could do is-- and this is what Maya was
saying previously--
you could make certain features, like taxes, very salient.
That's what we're going to look at next.
In addition, you could provide some information
when the correct response is known already.
That's one we're going to talk about afterwards
is the study by Hanna et al.
So that's kind of like when people
have certain types of information already
but then providing that information again or giving
that information in some sort of concise form
and potentially notifying people of the fact
that this information could be or should be important.
And then we now see people react to it.
That doesn't mean that that must mean that, before, they
were inattentive.
Another thing that people have done a lot is reminders.
Reminders often are sort of like--
you can think of the pieces like memory issues,
and people just forget things.
But in some sense, memory issues and attention issues
are very closely linked.
If you forget something, then you
don't pay attention to something.
So if I remind you of something, now you're
paying attention to, for example,
your savings or your medical adherence, like you should
take certain drugs and so on.
There's a number of studies that essentially provide reminders
to people.
And if these reminders have effects,
then that must mean that people were not paying attention
to those kinds of things, often presumably
because of memory problems.
They just forget sometimes.
OK.
So now let me start with a very simple model
to help us understand the results from the Chetty et al.
paper.
It's very simple and very sort of just sketched.
But I think it's actually helpful to see
what people are doing.
So consider a good with a value of V
inclusive of the price, which is the sum of two components.
The components are little v and o.
So there's visible and salient component v,
and there's an opaque component o.
OK.
And so if you're now inattentive,
the consumer, inattentive consumer perceived
value-- instead of perceiving the true value V,
the consumer perceives the value of V hat,
which is little v, which is a salient component.
So even if you're inattentive, the assumption
is the salient part of the good you always see.
For example, what color is the good or the like?
You always see that.
And in addition, the opaque component, the stuff that's
not salient, you're only going to pay attention
to the fraction of 1 minus theta.
So the degree of inattention-- so theta
is our inattention parameter.
And theta measures how much are you paying attention
to stuff that's not particularly salient.
So for theta equals 0, you're back to the cases before.
For theta equals 0, V hat equals V, which is essentially
just a standard case.
If theta were 1-- so theta is supposed to be between 0 and 1.
If theta is 1, then essentially you're
not paying attention at all to the opaque component.
And anywhere in between, essentially, then, you're
paying only partial attention to the opaque component.
So the interpretation is each individual essentially sees v--
sorry, sees o to some degree but processes it only partially
to the degree of theta.
Of course, whether you actually see it and not process it
or whether you miss it entirely is, in some sense,
a philosophical question.
But think about like, everybody has, at least in principle,
access to the component o.
But they only process and pay attention to it
only to some degree.
OK.
So Chetty et al. applies this model essentially to taxes.
So one very interesting feature about some taxes
is the fact that sales taxes are only added at the register,
right?
At least in most cases, you would shop in the store.
And then the sales tax, only at the end once you actually
go to the store, will be added.
Now, people are not--
people know.
When you ask people directly, what
is the sales tax in your state, people actually on average
are pretty good at knowing this.
So it's not like people don't know that there's a sales tax.
But they might just forget that there
are sales taxes for goods.
So now what you can do now is you can compare the demand
response to sales tax changes versus the demand response
to other price changes, right?
So if you see prices fluctuating in a store over time
or across goods, presumably, everybody
sees those price changes overall,
if these are price changes that are not
related to sales taxes, the reason
being once you're in the store, you're going to look at prices.
You're going to see is the price high or low
even before you go to the register.
So presumably, you see the price tag pretty much most
of the time.
In contrast, when you look at sales tax changes,
if the sales taxes go up for some reason
or if there's a sales tax for some items versus others,
you might just miss that at the time
when you're choosing your goods before you go to the register.
And once you're then at the register,
you might not even notice that you have paid the sales tax.
Or you might be surprised and just don't
change your behavior any more but at least notice it.
So now what did Chetty et al. do?
They have data on the demand for items in a grocery store.
And they have essentially the demand, D of V hat.
Remember, V hat is the function of the perceived value,
which I showed you here before.
Let me go back for a second.
So you see V hat here is v, which
is the salient component, plus 1 minus theta times o
as the opaque component.
So the demand for goods depends on the perceived value, V hat,
that people have.
And there's a visible part as the value V, which
is inclusive of the price.
So when you look at when you're in a store,
you look at the good.
You see the good.
You see whether you like it.
You see the brand.
You see the color and so on and so forth.
You also see the price, so the valuation
that you give or the value V that you draw from that
is essentially telling how much they want
to have this thing minus the price that you see,
which goes into the visible part of your valuation.
And then there's a less visible part,
which is just stuff that's essentially hidden.
And there's a bunch of different parts to that
that you might not pay attention to,
which could be ingredients or the like,
or was it organic or not and the like.
But in particular, the sales tax, right?
So if you think about your valuation,
you would have to essentially, however
much you like the good-- you have
to subtract the sales tax because you
have to pay taxes on that good.
And that's less visible to some people.
So you might not pay attention to it.
So in this case, it'll be V hat is v, the visible component,
plus 1 minus theta times o.
And that's just repeating what I showed you before.
And that equals v minus 1 minus theta times tp,
which is the sales tax.
And now to the extent that people pay attention to theta,
the sales tax might matter more or less.
There might be other opaque components
that are unobservable both to the experimenter
but also to the person.
They can abstract from that.
So for now, they can essentially say the less visible part
is only the state tax.
OK.
Any questions on this?
OK.
So now, and this is sort of like--
so now, essentially, what this gives us now,
we can essentially try to see if we have this--
how can we identify this parameter theta
by making things very salient?
And so the idea is now to make the tax fully salient.
Let me show you how this looks like in practice.
Here's the math.
But I'll go back to this in a second.
Let me just show you what this looks like in the experiment.
So the idea in the experiment is to say--
you see on the lower part here, you see a normal price.
You see an original price tag here.
This is what the price tag usually would look like.
So this would be an item.
I guess this is brushes.
This item would cost $5.79 usually.
And then what they did in the experiment,
they essentially added a tag where they said, now here,
%5.79 plus sales tax is $6.22.
And now they make it entirely salient
that there's a sales tax, and you make
the true price very salient.
OK.
And now the question is if you do
that, if we go from theta being, for example, say 5.5,
you only partially observe the sales tax.
If you go from that to making the sales tax fully salient,
what happens to people's demand?
And can you infer from that theta, what theta actually
looks like?
So let me go back to this.
So essentially, what we're trying to look at,
we're trying to look at a change in demand
when theta falls to 0.
Why does theta fall to 0?
The assumption here is that whatever
is theta people have before, so you might partially
or even not at all--
theta might be 0.5 or 1 or whatever for people.
But now the intervention that I just
showed you brings theta down to 0, right?
Because now it's fully salient to people
what the sales tax is.
And so the question is now, can we
have an expression for the change in log demand
when theta falls from whatever it is before down to 0?
So now what we have is the change in log demand
is the demand that we had before.
This is what I showed you before.
This was essentially demand as a function of V. Remember
what I showed you here before.
Give me one second.
I'll go back.
So what I showed you here, demand is a function of V hat.
And V hat is this animal here.
It's v minus 1 minus theta times tp.
Now, the question is, what happens to demand when
or log demand here-- forget about the log.
It's not that interesting.
That's just for math.
So here's the demand as a function of what it was before.
And here's demand when I now make
things very salient, right?
So now here in this case, theta equals 0.
And here, theta is whatever it had before.
Now when you have this expression, what
you can do is you can linearize that, take the derivative
and say, what is this difference?
Well, this difference is-- and you can do the math.
It's essentially theta times tp.
And then here, this is the derivative
with respect to theta.
And what this gives you essentially
is that the change in log demand is a function of theta,
a function of tau, which is like the tax,
and eta, which is the price elasticity.
So essentially, that's to say if you have now an intervention,
we can look at, how does demand or log demand change
when we do this intervention, assuming
that this intervention brings theta from whatever
it was before down to 0?
We can look at now what happens to demand.
That's delta log demand here.
That's just a definition.
And you can have that.
That's an expression of how we can relate that to theta to t,
which is like the taxes-- it is at something like 7%--
and then eta, which is the price elasticity of demand.
So that is to say, if we have this change in demand that we
observe from changing theta down to 0
and if we had the price elasticity from just
other variation in prices that we see in the world
and if you have t, which is just how much the tax is,
that would allow us to identify theta.
And that's what the experiment is trying to do.
So that implies essentially-- so we can just rearrange this.
We can just say theta is, just sort of rearranging things,
minus the change in log demand from this intervention divided
by t times the price elasticity.
OK, and that is just to say essentially
what we're trying to see is, intuitively, that's just to say
once we make things very salient going from things not being
salient to start with to making things very salient,
how much does demand change there?
And then we can look at, well, for--
in this case, I guess, this is the taxes made very salient.
And then we can look at, well, how
does this compare to other changes
in prices, assuming that essentially people are paying
attention to prices anyway?
So if you look at things becoming more expensive by 1%,
how much are people changing their behavior there?
And now we have to take into account that what's being
made salient here is the tax t.
And from backing out the relative changes in demand
for usual price changes versus making things salient,
we can now try to measure theta as how much did they
pay attention before.
So one way to say this is for example, if we make things very
salient and the change in log demand
did not-- there's no change in log demand,
what does that imply for theta?
What would we learn from that?
So what was the change here in demand at 0?
People did not change the demand at all
when you make things very salient
versus what it was before.
Or put differently, if theta equals 0 here,
then these two expressions are the same, which essentially
means that this thing here is also going to be 0.
So essentially, to the extent that our intervention induces
large changes in demand, that must mean that essentially,
people were very attentive to start with.
Essentially, if I'm making the prices very salient
and nothing happens, well, that means people were already
paying attention before.
Now, in the maximum case, if people
were paying no attention to prices before,
what would happen then?
Well, in that case, I guess-- oops, sorry.
In that case, theta would be 1.
So essentially, it would just be going
from-- we would look at what's the demand or change in demand
from going v minus tp to v, which is essentially
just a change in tp.
So that would be essentially say if the tax was 7%, now
we just have to look at what is the equivalent
effect of a 7% increase in the price, which
is exactly what we have here.
So essentially, just to summarize--
and I think the math is, in some sense, not that interesting.
But essentially, to summarize, it's
like the larger our reaction is to this intervention,
the more inattentive most people have
been before because if they're inattentive to start with,
they react more to making things more salient.
So let me show you what this looks like in practice.
Again, the goal here is to estimate a change in demand
from making taxes fully salient.
Again, here's the original tag, and here's
the experimental tag.
It's very, very salient, very, very clear, and very hard
to miss for people.
And the assumption essentially is
that people pay now full attention to this new tag.
They have a three-week period in which--
and this is an experiment in California.
They have a three-week period in which
they modify price tags of certain items
so that they go essentially to different stores.
They pick one store.
And then essentially, they modify the price tag
only of the subset of randomized goods.
And they make the after-tax price salient in addition
to the pre-tax price, right?
The pre-tax price is already very salient here.
In addition, they make the after-tax price very salient.
And now they're going to do what's
called a triple-diff estimate, which is, in some sense, a very
funky or fancy word just to say what we're going to do
is we compare the sales or the demand
during the treatment periods to the following.
So there's a treatment period.
We compare how much of certain goods have been treated.
How much do the sales change compared to the previous week
sales for the same items?
Second, we're going to compare them
to sales for items in which the tax was not made salient.
So there's some goods in the store for which the tax was not
made salient.
And then finally, there's going to be control stores.
So we're going to look at essentially,
in the stores that receive the treatment
or in the store that receives the treatment, what happens
to the goods that receive the treatment compared
to the goods that don't receive the treatment?
We compare that to demand before the treatment was
enacted for both of those types of goods.
Essentially, what's the relative change
in demand for the treated versus the non-treated items before
versus after?
So that's essentially what people
would call a diff in diff, like difference in differences.
And in addition to that, they compare that difference
in differences to the same difference in differences
in the control stores.
So let me show you exactly what this looks like.
So this is a bit of a messy table
or a table with a lot of information.
But it's in fact quite simple.
So what we have here is at the top is a treatment store.
And at the bottom, there's some control stores.
So in the control stores, nothing has been changed.
So there's no experiment.
There's no additional tax and so on being added.
In the treatment stores, there's going to be control categories
and treated categories.
Notice that they didn't fully randomize all the goods.
So it's not like if there's one brush next to another,
one brush has taxes versus not.
Presumably, because they're trying to minimize spillovers
in some sense, if you only make this tax salient for one
good that's next to another good,
people would get very confused because they're like, well,
why does this one have taxes made salient and then
the other one not?
So now this is across categories where people maybe
only pay attention to certain goods in certain categories
to start with.
So what we're seeing here is now here,
these are the control categories and the treated categories.
And we can look at what's called the difference in differences.
We can look at the change in demand in the treatment stores.
What we're going to look at is essentially
the change in demand in the control categories
and the treatment categories.
So what we see here is we can compare
how much is sold in the experimental period, which
is this row here, compared to our baseline.
What we see is essentially demand in the control
categories was going up a little bit by 0.84.
That's just because of seasonalities.
Maybe people were just buying more anyway
for whatever reason.
And in the treated categories over the same period,
comparing essentially the experimental periods
to the baseline period, demand went down.
So now the difference in differences estimate
is essentially the change in demand in the treatment stores,
comparing the treated categories compared to the control
categories, which is just the difference
between this column and this column,
which is minus 2.14 units.
OK.
So that's essentially, how much did the demand
change before versus after in the treated categories compared
to the same change in the control categories?
So that's essentially a difference
in differences estimator.
Now, they also have the control stores.
Why would we want the control stores, as well?
Why is that helpful to have?
Suppose that improved sunscreen, and now it's getting warmer.
It's really hot, and everybody was out buying sunscreen.
Then you see essentially people's demand
in the control categories.
The treatment category goes up by a lot
or goes down by a lot for whatever reason.
Suppose it's umbrellas, and one week was really rainy,
and the other one was not rainy.
And we see now essentially seasonal or other differences
over time in some of the categories that would,
even if it's randomized, it could just
happen to be the case.
So that would not have to do anything with a sales tax
being salient.
That's just by chance.
So now it's very nice to have some control stores
where we can look at like the same difference in difference
estimates and some of the control stores, in some sense,
like a placebo.
They can do the same things.
There's going to be the control categories and the treatment
categories.
Notice, to be very clear, in the control stores,
the treated categories do not receive any actual treatment.
So we can do the same difference in differences.
And what we see here is now that there's essentially
no difference here.
So the demand in the control categories
went up a little bit for whatever reason in the treated.
And this is a little bit smaller than in this other store.
This difference is not statistically significant.
But anyway, the control categories go up a little bit.
The treated categories go also up a little bit.
When you do this difference in differences estimate,
you find essentially no difference.
In the control categories, there's
no change in the treated categories
compared to the baseline compared to the control
categories.
So difference in difference estimate in the control
category is essentially 0.
And now what you can do is essentially the difference
in differences estimate.
You can compare.
You can subtract this number here
minus this number here, which gives you
the triple-diff estimate, which essentially
is the relative change of treatment versus control
before and after and treatment versus control stores.
It's a little bit lots of differences in your head.
But I hope this comparison from the table makes it clear.
Any questions on the estimate or the procedure
that they're doing?
OK.
So what we see here now is essentially now making
these taxes salient in the treated categories
in the treatment stores reduces demand, right?
Because essentially, demand goes down.
Why does the demand go down?
Well, the perceived price that people face has now gone up.
And now they buy less of these goods,
presumably because before, they were not paying attention.
Now the price goes up.
And now, essentially, demand falls, as it should,
because now things are more expensive.
And this is here the result. The average quantity sold decreases
by 2.2 units-- this is units of the goods--
relative to baseline level of 25.
That's an 8.8% decline.
And now we can use our own formula
and compute the degree of inattention.
Essentially, now we can say, OK, now we know what the tax was.
The tax was 7.375%.
We can estimate the price elasticity in some other ways.
Essentially, we can say, what happens if prices go up
by 1% for other reasons?
What if the salient component that's already salient goes up?
This is week-by-week variation across stores.
So if the prices go up, what's the price elasticity?
And the estimate of those price elasticity
is also given from other variation.
That's 1.59.
And now we can essentially back out theta.
Essentially, what we're trying to ask
is we have a change in 2.2 units that is making prices salient.
Now the question is, well, how large of a change
is it relative to a change in prices of 1%, 2%, and so on?
We know that essentially the price elasticity is 1.59.
So we can essentially just back out theta.
And so what we get from this formula
now is that theta is about 0.75, which says that consumers react
to price changes due to sales tax changes only a quarter as
much as to other price changes.
So essentially, consumers are very inattentive, in fact,
to sales taxes, to sales tax changes.
In fact, they only perceive a quarter
as much as any other price changes in the world.
And that's really saying, look, people really
seem to be missing these things that are not salient.
Now if you make them salient, people change their behavior.
Therefore, they must have been inattentive to start with.
In addition to that kind of evidence,
Chetty et al. also have some evidence
on using non-experimental variation.
And in some sense, you could say the evidence
that I just showed you from the store is a little bit
weird because, in some sense, you see these different tags.
And maybe the tags raise attention
to the price even regardless of the tax.
And it's a little bit weird in some ways.
So it's quite nice to have some complementary evidence
of a non-experimental panel deliberation.
And so what they do is they look at beer consumption.
And it turns out beer, tobacco, and other types of goods
have two types of taxes levied on them.
They have an excise tax, which is included in the price.
This is highly salient during choice the process
because essentially it's in the price already.
So if taxes go up, essentially, the price goes up.
And people will notice if they pay attention
or since they pay attention to prices, since they
like the price tag already.
And then there's a sales tax.
This is the tax that we were just talking about before.
That's essentially very opaque during the choice process,
as we just showed.
And now we can look at variation across states
and over time of changes in excise taxes and sales taxes.
And we can look at, how much do people
react to excise taxes relative to how much people
react to sales taxes.
And that relative reaction will tell us, again,
something about theta.
And what Chetty et al. finds in here is a table for that.
Essentially, when you look at changes in excise taxes,
this tax is very salient.
The price elasticity is above 0.8 or 0.9.
So essentially, when the price goes up by 1%,
people react by about almost 1%.
In contrast, there's some differences in estimates.
But once you control for things properly,
people essentially do not react to the sales tax at all.
Maybe a little bit, but overall, the number's very, very low.
And now, essentially, the ratio of these types of reaction
tells you how attentive people are.
Essentially, if you divide, say, for example--
if you took column number three, if you divide 0.003 by 0.86,
and you have to do a little bit of additional math
that's uninteresting-- you essentially
will get a result that, essentially, people do not
pay attention to sales taxes.
1 minus theta is eventually close to 0.
Put differently, the degree of inattention is almost 1.
Theta is almost 1.
So essentially, people do not pay attention
to these types of taxes.
Inattention is almost complete.
So there's substantial consumer inattention
to non-transparent taxes.
So what I've shown you so far is, essentially,
the existence of inattention.
It doesn't say why people are inattentive.
It could be people just can't do the math in their head.
It could be people don't want to bother with it.
They're sort of saying, well, it's kind of a small change.
So why do we really care?
It could be that people who buy alcohol half of the time
are drunk, and they don't pay any attention.
There's no modeling in any way of, why are people doing this?
This is just saying this shows the existence of inattention
in those kinds of consumer choices.
It doesn't say why people are inattentive.
And you might say, well, 7% of a tax
is kind of a small distortion.
So it might be actually optimal to miss that,
which is a reasonable approach.
It is probably quite a bit of money
and quite a bit of distortion if you think
about it and you actually--
7% is not nothing.
But if you have a lot of money anyway,
you might as well just not pay any attention to that stuff
and if that helps you pay attention to other things.
Notice that even then, that shows
the existence of inattention.
It's just a bit of a question, like,
how important is inattention?
And this actually gets me to the next point,
which is a question of, why should we care
about inattention to taxes?
Why is that important or interesting potentially?
Question exactly is, who's paying attention?
Who's not paying attention?
And then who's sort of distorting
their behavior potentially?
There's lots of interesting issues about heterogeneity
and who's paying attention.
Let me talk about this in a second.
Let me ask differently.
Why is it that some taxes, the excise taxes, are very salient?
And why is it that other taxes are not salient?
What do you think about that?
Is that an accident?
Or why is it that the taxes for alcohol and tobacco,
et cetera, are very salient?
And why is it that other taxes for shampoo or
whatever are actually not salient?
There's two simple objectives if you took a public economics
class, if you took John Gruber's class,
but also if you took 1401 or 1403.
The reason why the government levies taxes is--
one big reason is to generate revenue, right?
The government needs money.
Somehow, we need to tax people.
And the issue, of course, is that if you levy taxes
on some goods versus others, that
can distort consumer choices.
And there's essentially some theorems
and some considerations about which goods should you tax.
And ideally, you would tax goods that people
are consuming anyway.
Essentially, what you want is people make--
so essentially, when you have taxes on some goods
but not on others, if people have different price
elasticities on some goods versus others
and if you increase one good or all goods by a certain amount,
if people have different price elasticities,
then you might distort their behavior.
So if you increase and you start taxing one thing and not
another, people might shift to the other good.
And we don't want that because, presumably, people are already
optimizing to start with.
Now, if people are inelastic to certain goods,
if people need certain goods anyway
and they buy them anyway--
and the last thing, essentially, there's public goods.
Public economics would tell you or some theories would tell you
you should tax these goods more.
Now, distortion, when people are-- so the distortions
are lower if people don't fully react to taxes.
That could be if, for example, you started taxing bread,
for example, while everybody-- or certain goods like potatoes,
where everybody needs to buy these goods anyway
because people need to eat--
well, then, there would be very low--
these goods would be very inelastic.
And that's because they need those things.
Not because they're inattentive, but just
because they need these types of goods.
Now, there's obviously issues with poverty.
We don't want to tax the poor too much.
But in general, they want to tax things that are inelastic.
And so in a way, if people are inattentive to the taxes,
in a way, that's great because now they're
not distorting their behavior.
And we can still get money from them.
So in some sense, actually, some of the inattention
for that purpose might be actually good
because now people are not distorting their behavior
by looking at those prices.
So being inattentive in some ways is good.
But exactly as Maya was saying, for some goods--
and these are often labeled as sin goods or the like,
where there's either externalities or internalities.
For example, if you think about tobacco or alcohol,
there are externalities.
Tobacco, for example, secondhand smoking is bad for others.
For alcohol, there's often externalities
in terms of drunk driving or violence or the like.
So the government wants to increase the price of alcohol
because when people are making choices of how much alcohol
to buy, they might not take into account the effects of alcohol
on others.
By internalities, I mean people might not necessarily
take into account the effect of alcohol or tobacco
on themselves.
This is what we discussed previously.
This could be because of present bias.
This could be because of biased beliefs or the like.
Essentially, people might hurt their future selves.
And the government might say, well,
let's increase taxes because their future sales--
people might like that there might
be a way of helping people, for instance,
deal with self control problems.
So here, the government explicitly
wants consumers to react to the taxes.
The point is not to make money from people.
And in fact, sometimes you're worried
about making too much money from people.
The point here is really to change behavior
to reduce the behaviors that are being taxed.
So you want to make such taxes particularly salient.
Ready?
Now, look at the taxes on alcohol versus the taxes on--
some of the excise taxes versus the sales taxes.
The excise taxes are precisely salient because we
want people to react to it while the sales taxes are not.
Of course, there's variation across places.
But it's not an accident that we see this in the world the way
that is.
Now, one thing that's quite interesting now is--
and I think José or [INAUDIBLE] was saying that.
It's like when consumers are heterogeneous,
then there's a lot of quite interesting issues.
For example, if you have the poor paying more or less
attention compared to the rich or if only a subset of people
pay attention to those goods, then in a way,
you would find that the average elasticity is still quite low.
But some people are actually distorting their behavior
quite a bit, and others do not.
And that gets relatively quickly quite complicated.
And you could then get into situations
where you make some people a lot worse off and some people
better off when making something salient versus not.
Any questions on all of this?
OK.
So then we get to the next question.
This is getting a little bit at the question that
was asked previously about, can inattention or attention
have large effects?
And so on the one hand, you might say, well,
people's choices-- for example, consumption patterns--
are distorted due to limited attention.
But you might ask, well, if it's really true
that people's consumption patterns have really distorted
that much, if I'm so much worse off by not paying attention
to things, well, eventually, I'm going to notice this.
Somebody is going to tell me.
Or in a way, I notice myself eventually
that I'm doing things really worse compared to my friends.
And eventually, if things are really distorted a lot,
I might pay attention to it.
So the underlying idea is that, potentially, people
are actually inattentive in the sense of saying,
look, people's attention is limited in some ways.
But it's optimal for people to pay attention
to things that are really important.
And there, the underlying question
is, what is salient to people?
And how do people decide what to focus on?
And won't people pay attention to important things
anyway if they have to?
And so then the question is, well,
how is it possible that inattention could
have large effects anyway?
And so the next paper is a good example of that.
And here's a very intuitive example of why that might be.
So consider the following situation.
You have been getting headaches.
You go to the doctor.
And the doctor asks you whether it gets worse
after eating certain foods.
And so what are you going to say?
Well, the answer will probably be like, I don't know.
And why is that?
Why might you just not even know the answer to that question?
An underlying theory in your mind
of why you might be getting headaches.
And you might just not have a theory
that it's related to your food consumption.
So while you have lots of data in front of you--
you eat every day, you get headaches on some days
and not on others-- you could surely pay attention to it
if you wanted to.
But it's not even a theory in your mind,
so you won't even encode the relevant information
if you don't expect to have food allergies or gluten
allergy or the like if you don't expect
that to be a likely cause.
Then you're never going to actually pay attention,
and you get infinite amounts of data on every day and headaches
and food consumption.
But you're never going to notice because you
don't have a theory in your mind that that might be the case.
And so there's a relationship between attention and memory.
You only remember or pay attention to stuff that
actually are theories of yours.
And then you'll remember those things
that you actually paid attention to in the first place.
And so selective attention, then,
may have persistent effects on what we learn.
Essentially, you could have unlimited amounts
of information in front of you.
And you will never learn because you never
just had it on your radar that this information is actually
relevant for the issue at hand.
And Josh Schwartzstein has a very nice model
that illustrates that.
Another example is from medicine.
Many women died from childbed fever
at hospitals in the mid-19th century.
The popular theories were bad smells
at the hospital, presence of male doctors wounded
the modesty of the mothers.
That's, of course, nonsense.
The true explanation is germs.
Doctors didn't wash their hands.
And again, it's something-- that's not a tricky thing
to figure out if you have the idea, if you
have the hypothesis or the idea that this could be important.
And presumably, some doctors are washing their hands anyway
and sometimes are not, and they would have a lot fewer deaths.
But nobody was noticing because, again, just nobody
was paying attention.
So once you have the right theory in mind,
then you can test it.
And then, of course, you can gather the right information
and pay attention to the right information and learn.
Now, the basic model from Josh Schwartzstein-- beliefs
today matter for what is being attended
to today, which then affect people's beliefs tomorrow.
And now if you don't attend to the right things,
if your model of the world is the wrong model,
you might never learn to attend to important aspects
of the world.
And so then forecasts and beliefs
may be biased and persistently biased in a systematic fashion.
And you might persistently misreact and misattribute
causes to unimportant variables because you have never
even considered the idea of the correct model of the world.
And so now the paper I'm going to show
you is an example of that.
This is seaweed farming in Indonesia,
which is not immediately obvious why that's related.
But I'll show you in a second.
So this is what seaweed farming looks like.
I'll give you this relatively briefly.
But essentially, it's like, at some beaches,
you can grow seaweeds in these rows.
And you see these round things here,
which are essentially pods.
And so there are many factors that are
important in seaweed farming.
Essentially, it's like these pods, which are essentially
these round things that you see here,
they're essentially grown in different lines.
And so if you're seaweed farmers,
what's really important is line spacing--
or potentially important is line spacing, pod spacing, and pod
size, how we got these pods.
Now, how does seaweed farming actually work?
I've never done seaweed farming myself,
but apparently this is how it works.
So farmers use what's called the bottom method, which
is they drive wooden stakes in shallow bottom near shore,
and they attach lines to these stakes.
And they take raw seaweed from the last harvest
and cut it into pods, like these kind of roundish things.
And the pods are planted by attaching them
at a given interval on the line from the sea.
And at low tides, farmers tend the plots.
And so the seaweed is then harvested after 30 to 40 days.
And so now many dimensions could matter-- the pod size,
the distance between the lines, the distance between pods,
timing, and so on.
One nice thing about seaweed is there's many different pods.
You can actually try and learn and estimate
the importance of these factors over time
if only you paid attention.
But the question is, which of these factors are important?
And are people paying attention to those factors?
And so what the experiment now is doing
is there's lots of farmers in the experiment that
are quite experienced.
They have been doing this for a long time, 18 years of farming.
Many of them or the vast majority are literate.
So these are people who should really
know what they're doing in their seaweed farming experience.
And so the enumerators went to visit these farmers
and to measure and document their farming methods.
And when you asked them about current pod size,
you just ask them how big are your pods,
people just don't know the answer to.
They also don't know the answer to,
what's the optimum pod size?
When you just ask them how big are your pods when you
plant them, they don't know.
When you ask them what's the best way to do it,
they don't know.
Importantly, they know exactly the answer to other questions.
They know the length of the typical line.
They know the distance between the lines.
And they also have very clear ideas
of what's optimal to do so.
But they seem to essentially neglect the pod size dimension
entirely when they're thinking about what to do.
And so in the experimental trial now,
they did essentially different treatments.
And the treatments were essentially such
that farmers were provided experimental variation
in the different pod sizes and essentially induced
to experiment with pod sizes.
And in some cases, farmers were just left on their own.
They were just induced to do this experiment.
And the question was like, now will farmers
learn from their own in this experiment?
And then in addition, they also have an information condition
where they then summarized that information to the farmers
in addition.
So the question is now, once farmers
are induced to experiment, you surely
would think that farmers would learn now
that they're given all the information that they need on,
like, here's the different pod sizes.
Here's the different profits that you
get from the different types of pods.
Now they might learn on their own.
But if you don't attend to pod size in the first place,
if you think it's irrelevant anyway,
even if you are induced to do the experiment,
you're not going to learn at all.
And so then they did essentially these follow-up surveys.
And then we'll just skip.
So now what they do is they also go through an information
provision where they essentially tell farmers the [INAUDIBLE]
they were doing with everybody.
But in addition, they also provided information
and did some simple calculations on which
is the best combination of pod size and distance.
Notice that farmers are literate.
They're able to do this on their own.
But the experiment was just providing this information
to farmers explicitly with a recommendation
about what's the pod weight and what is the optimal distance.
And so now what the experiment finds
is large gains from changing the farming methodology.
And the trial participation itself only
has an insignificant effect.
That's to say, in addition, then,
summarized data for people has much larger effect.
Essentially, focusing people's attention to things
that they should already know changes their farming behavior
a lot.
And it's essentially evidence that people were not
paying attention in the first place
even if you make them participate in a trial
where they should have really or could have,
at least, learned things on their own.
There's large impacts of the trial
if the data from the trials is presented to farmers.
There's no impact of the trial on dimensions
that farmers had already noticed previously,
presumably because they're already paying attention
and were optimizing.
So now what did we learn from this?
And let me quickly summarize and let you go.
So we have systematic learning failures
even though all the information was available.
So farmers simply did not pay attention
because they didn't think that pod size was
relevant in any way in their lives.
And that's a potential explanation
why people might not pay attention
even to important information because if your model
of the world is just wrong, why would
you even think that this is important?
And the problem here is then there's never an opportunity
to actually learn.
You never even collect information
that might reject your model because you're
convinced that your model is right in the first place.
And so then lack of attention might generate arbitrarily
large welfare losses.
You can really screw up big time for a long time
and never really change your behavior because, essentially,
you never learn.
You never even pay attention to any information
that you might have available that says your model is wrong.