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PROFESSOR: Welcome to
Lecture 15 of 14.13.

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Today we're going to talk
about utility from beliefs.

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Overall, lectures 15 and 16
are talking about utility

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from beliefs and learning.

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Well in the previous
lecture, we talked

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about attention and
the idea that attention

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might be a limited role-- so
you might not have the capacity

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to attend as much as we can.

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And then thought a little bit
about, what kinds of things

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are people paying attention to?

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And can it be that
people systematically

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attend to the wrong things
and miss important things

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in the world?

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Today we talk about different
deviations from, perhaps,

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optimal belief or optimal
information acquisition, which

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is people might derive utility
directly from beliefs that

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therefore have potential
incentives to deceive

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themselves in certain ways.

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Next time, we're
going to talk more

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about learning--
sort of deviations

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or systematic deviations
from Bayesian learning.

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So to summarize
today, we're going

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to talk about the
utility from beliefs.

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People directly deriving
utility from beliefs,

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from what they think
about the world,

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about themselves, what's
going to happen in the future

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or how smart they are and so on.

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On Monday, we're going to talk
about non-Bayesian learning--

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this idea that people
essentially have

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trouble being visual learners.

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Being Bayesian is quite hard.

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You may have taken
probability theory and so on

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and have learned quite a bit.

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But even as a very smart
and educated MIT student,

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there will be Bayesian
learning problems

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that are way too hard once you
have several variables, lots

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of information.

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It's just really hard to do
these things in your head.

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And people might just
not be very good at it

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and then sort of use
heuristics and biases instead.

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And then after that, we're
going to talk about projection

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and attribution bias,
which essentially,

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if people have
trouble predicting

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how they might feel in
different states of the world--

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if you're hungry, it
might be hard for you

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to not think about
being hungry or think

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about how it might feel.

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But you're not hungry.

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If you're sad, it
might be very difficult

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for you to understand
how it feels

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when you're happy and so on.

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And so I should say,
on Thursday and Friday,

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tomorrow, you're going to talk
in recitation about Bayesian

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learning, which is
sort of like, how

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do economists or statisticians
think you should optimally

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learn?

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What's the Bayesian
benchmark here?

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And we're going to talk
then about-- on Monday--

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deviations from that.

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OK.

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So the first big picture
overview is like,

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why might people miss
information and fail to learn?

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What are potential reasons?

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Why might people do that?

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And we talked about
true potential issues

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already last time.

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One is, very broadly,
attention is limited.

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That's to say, there's so much
information in the world that

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we just cannot
attend to everything.

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Right?

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And so one specific example
was inattention to taxes.

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But you could
think about there's

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lots of different
prices in the world.

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It's just way too much
information in the world

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for you to attend to everything.

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And so one example
that we talked about

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was inattention to taxes.

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It's saying that taxes that are
not included in the sales price

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might be easily
missed by people.

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And we have this very nice
paper by Chetty et al.

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that demonstrated that--
that people essentially

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systematically under-estimate
or under-appreciate taxes

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that they are exposed to.

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People pay more
and more attention

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to taxes that are directly
included in the sales price

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compared to taxes that are
only added at the counter.

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And of course, both of
them you have to pay.

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And so you really
should not really

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under-appreciate those
taxes, because that's

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just expensive for you.

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We did not get much into
why are people doing that,

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but more like show the
existence of people

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seem to be missing those taxes.

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Then we talked about reasons why
people might systematically--

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and even in the presence of
lots of data in front of them--

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not update properly, even if
they are, in fact, Bayesians.

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And the reason
might be that they

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might have the wrong
theories of the world.

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You might think that
certain variables are just

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not important for
your well-being

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or for any important
things in the world,

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and therefore, you
have essentially--

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since your attention is
limited, you will only

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collect some information.

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You only focus your
scarce attention

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and memory to what you think is
important things in the world.

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And so now if you do that,
you might systematically

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miss or not collect data that
would help you essentially

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improve your theories
and therefore,

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even in the very long run,
even when you get lots of data,

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you will not update.

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Notice that that's
quite different

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from rational inattention.

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There is rational inattention
theories would say,

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well people's
attention is limited,

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but they focus
attention to whatever

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is most important for them.

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So it can't really be
that they have huge losses

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from a lapse of attention,
because if they were, then

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they would direct their
attention to something that

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could be potentially important.

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In contrast, the
"Learning by Noticing"

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paper, the theory paper by
Hanna et al. that we discussed,

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provides a reason
why people might not

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pay attention to stuff that's
really important for them.

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And so, again, if
your theory says

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that certain aspects or certain
information is not helpful,

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you would not pay attention to
those pieces of information.

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And if you don't pay attention
to those pieces of information,

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you will never update
your own theories

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and your own theory
will essentially

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persist for a long time,
potentially forever.

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We're going to talk now
about two other reasons

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for potentially wrong beliefs.

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One is anticipatory utility.

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This is, essentially,
people like to look forward

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to good things in the world.

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Suppose you have a vacation
coming up in six months

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from now.

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You might think about this
positive event going forward.

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Essentially, good or bad events
in the future that might happen

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and you might derive utility
from those events already now.

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Second, there's what people
call ego utility, which

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is, people derive utility from
thinking that they are smart,

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good-looking, and so on.

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So essentially,
they derive utility

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from thinking positively
about themselves.

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Now for both of those
kinds of pieces of utility,

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people now potentially have some
incentives to delude themselves

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and to think that
things are perhaps

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better than they actually
are, because that

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will make them happier.

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And so then often there
is, at the end of the day,

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there's some trade-off
between having

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overly positive or
optimistic beliefs will

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make people happier.

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They feel good about themselves.

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They feel about good things
happening in the future.

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But that may come at the cost
of not preparing or taking

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wrong actions because people
are sort of overly optimistic.

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Right?

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So one example would
be people might not

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get tested for certain
diseases because they want

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to think that they're
the healthy people

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and want to be happy
about the future

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and look forward to
a positive future.

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But of course, if they
were getting tested,

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that would help them to take
optimal actions-- potentially

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medication or any
other actions reacting

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to the potential disease
that they may have.

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And for ego utility,
for example,

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if you always think that you are
smarter than you actually are,

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well that might make you happy.

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But at the same time, that
might have come at some cost

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and you might not
prepare properly

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for some exams or
interviews or other things.

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You might just miss
important things that

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might hurt you along the way.

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And then finally,
the last reason

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that we'll talk about next week
is people might simply just

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be bad at Bayesian learning.

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Then there's no utility from
beliefs or the like involved.

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It's just a lot of the
computational issues

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that we ask people to
do are just really hard

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and people might be bad at that.

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And therefore, people use
heuristics and biases.

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And then systematically, most
of the time these heuristics

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and biases are quite
helpful and help people

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making reasonable decisions.

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But then often these heuristics
and biases are, in some ways,

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systematically wrong.

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In some cases-- and
we can then think

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about some systematic
errors and perhaps offer

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some ways in which
you can improve

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people's decision-making
by avoiding these errors.

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Now let's talk about
utility from beliefs.

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So it's important to understand
that economists typically

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define utility functions
over outcomes, such as money,

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consumption, health.

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Think of these things
as things that people

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consume one way or the other,
or things that they can usually

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measure at some point.

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So you can look at it
like, you have money.

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Then if you have money, you will
spend it on consumption goods.

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It could be apples and
bananas, of course.

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It could be also like haircuts
or other services or health,

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for example.

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And I can measure whether
you have good or bad health.

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Usually we think about
some outcomes that

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could be at levels of outcomes.

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So essentially, like three
apples or five apples or seven

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apples are the arguments
of utility function.

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It could be also-- as we
discussed when we talked about

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reference-dependent utility--

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it could be in part being
deviations from some reference

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point or changes over time.

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But importantly, here,
the arguments-- or goods

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and services, essentially,
are the arguments

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of the utility function.

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Instead, another
source of utility

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could be beliefs
about such outcomes.

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So now it's about what might
happen either in the future

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or what's happening right now.

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And you might directly derive
utility from such beliefs.

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Now such utility from beliefs
can be a very powerful source

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of utility.

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One example, for
example, would be

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a high-profile public speech.

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Suppose you have to give
a public speech in front

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of the entire universe.

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Now of course you might
sort of derive utility

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directly from that
experience itself.

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You might like it a lot.

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You might find it
very stressful.

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So the 10, 20, 30,
whatever minutes--

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however long the speech is--

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might give you positive
or negative utility.

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But perhaps the utility
of that experience

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itself might be or
could be dwarfed

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by the stress and anticipation
derived beforehand

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from anticipating it.

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That is to say, you
might think about it.

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You might prepare about it.

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You might worry about it.

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You might not sleep at night.

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So there might be lots of
stress or positive excitement

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and anticipation.

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Every day-- if you give the
speech sometime in September,

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every day until
September you're going

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to think about it
positively or negatively.

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And you might derive positive
or negative anticipatory utility

255
00:11:31,390 --> 00:11:32,203
from it.

256
00:11:32,203 --> 00:11:34,120
There's another part of
utility that we're not

257
00:11:34,120 --> 00:11:34,953
going to talk about.

258
00:11:34,953 --> 00:11:36,340
It's utility from memories.

259
00:11:36,340 --> 00:11:38,345
So you might afterwards
look back and say, oh,

260
00:11:38,345 --> 00:11:39,220
that was really nice.

261
00:11:39,220 --> 00:11:41,850
And you have a video, and you're
going to enjoy it, and so on.

262
00:11:41,850 --> 00:11:44,183
We're going to not talk about
that, but that's sort of--

263
00:11:44,183 --> 00:11:48,230
backward-looking utility could
be quite important as well.

264
00:11:48,230 --> 00:11:52,270
Now when you think about utility
from beliefs, one way to think

265
00:11:52,270 --> 00:11:53,682
is that this is
all in your head.

266
00:11:53,682 --> 00:11:55,390
But it turns out the
utility from beliefs

267
00:11:55,390 --> 00:11:59,080
can actually even affect
physical outcomes.

268
00:11:59,080 --> 00:12:01,990
In particular,
there's a large body

269
00:12:01,990 --> 00:12:05,440
of research on
placebo effects, which

270
00:12:05,440 --> 00:12:08,470
is defined as a treatment
that can help patients merely

271
00:12:08,470 --> 00:12:11,500
because he or she
believes it will.

272
00:12:11,500 --> 00:12:14,620
That is to say, if you give
people a placebo or a sugar

273
00:12:14,620 --> 00:12:17,620
pill, something that essentially
has no active ingredient,

274
00:12:17,620 --> 00:12:23,270
and tell them that this is,
in fact, an effective drug

275
00:12:23,270 --> 00:12:27,290
for something, that drug
itself, relative to control,

276
00:12:27,290 --> 00:12:30,170
might have treatment effects.

277
00:12:30,170 --> 00:12:38,680
Now that often is the case for
things like pain medication.

278
00:12:38,680 --> 00:12:41,540
Although usually we think pain
medication-- if you give people

279
00:12:41,540 --> 00:12:46,250
placebo pills, compared
to actual pain medication,

280
00:12:46,250 --> 00:12:49,580
these drugs are about a third
as effective as pain medication.

281
00:12:49,580 --> 00:12:52,018
Depends, of course,
on the dosage.

282
00:12:52,018 --> 00:12:54,060
So that's quite powerful,
but then you might say,

283
00:12:54,060 --> 00:12:55,400
well that's only
in people's head,

284
00:12:55,400 --> 00:12:56,775
and maybe people
just say they're

285
00:12:56,775 --> 00:12:59,777
happier or less in pain,
when, in fact, they're not.

286
00:12:59,777 --> 00:13:01,610
There's also some studies
that have actually

287
00:13:01,610 --> 00:13:04,040
found some physical symptoms.

288
00:13:04,040 --> 00:13:05,960
So you give people a
placebo pill and there's

289
00:13:05,960 --> 00:13:09,230
actually physically, in
some measurable ways--

290
00:13:09,230 --> 00:13:11,540
hard measures, not just
self reports-- people

291
00:13:11,540 --> 00:13:12,450
are doing better.

292
00:13:12,450 --> 00:13:16,710
So the placebo effect can
be, in fact, quite powerful.

293
00:13:16,710 --> 00:13:22,730
So when you now think overall
about sources of utility,

294
00:13:22,730 --> 00:13:25,220
it's hard to imagine, in
fact, any source of utility

295
00:13:25,220 --> 00:13:28,340
that's not influenced to
some extent by beliefs.

296
00:13:28,340 --> 00:13:31,950
Often it's about how you
look forward to some things.

297
00:13:31,950 --> 00:13:34,460
It's not just about going
to a restaurant or a date

298
00:13:34,460 --> 00:13:36,110
or having fun with friends.

299
00:13:36,110 --> 00:13:43,060
A lot of it is also just the
anticipation of all of that.

300
00:13:43,060 --> 00:13:43,630
OK.

301
00:13:43,630 --> 00:13:46,810
So now more
specifically, what do we

302
00:13:46,810 --> 00:13:49,300
mean by anticipatory utility?

303
00:13:49,300 --> 00:13:53,925
So many emotions in
particular are intimately

304
00:13:53,925 --> 00:13:57,280
linked, related to what a
person thinks about the future.

305
00:13:57,280 --> 00:14:02,020
And you think about hope, fear,
anxiety, savoring, et cetera--

306
00:14:02,020 --> 00:14:04,090
a lot has to do
with some stuff that

307
00:14:04,090 --> 00:14:06,910
might happen in the
future, some events that

308
00:14:06,910 --> 00:14:10,160
might happen for sure, or
some events that could happen

309
00:14:10,160 --> 00:14:13,160
but we're just worried
about, such as when

310
00:14:13,160 --> 00:14:15,888
people are afraid and
anxious about certain things.

311
00:14:15,888 --> 00:14:17,930
Those are actually things
that might happen, even

312
00:14:17,930 --> 00:14:21,140
with a pretty low probability,
yet people right now

313
00:14:21,140 --> 00:14:28,270
might be for sure quite
anxious or worried or afraid.

314
00:14:28,270 --> 00:14:31,630
Now then how do we
define and think

315
00:14:31,630 --> 00:14:33,700
about anticipatory utility?

316
00:14:33,700 --> 00:14:36,700
Well it's utility derived
now from anticipating

317
00:14:36,700 --> 00:14:37,490
in the future.

318
00:14:37,490 --> 00:14:39,220
So there's stuff
that, in the future,

319
00:14:39,220 --> 00:14:42,190
enters your utility
function directly.

320
00:14:42,190 --> 00:14:45,520
And those events that
will happen in the future

321
00:14:45,520 --> 00:14:47,380
could be consumption,
could be also

322
00:14:47,380 --> 00:14:50,080
services, could be like bad
shocks or any things that

323
00:14:50,080 --> 00:14:52,120
will happen in the future.

324
00:14:52,120 --> 00:14:54,490
Right now, in the
current period,

325
00:14:54,490 --> 00:14:56,620
you're already feeling
good or bad about it.

326
00:14:56,620 --> 00:15:00,580
Or something that will
happen one or several periods

327
00:15:00,580 --> 00:15:01,540
in the future.

328
00:15:01,540 --> 00:15:04,630
And anticipatory utility
is a prime example

329
00:15:04,630 --> 00:15:06,550
of utility from beliefs.

330
00:15:06,550 --> 00:15:10,407
Now how might anticipatory
utility affect behaviors?

331
00:15:10,407 --> 00:15:11,990
You can think about,
broadly speaking,

332
00:15:11,990 --> 00:15:14,742
two classes of implications that
we are going to think about.

333
00:15:14,742 --> 00:15:16,450
There are sort of
other potential effects

334
00:15:16,450 --> 00:15:17,960
that might be there.

335
00:15:17,960 --> 00:15:23,320
So the first one is people, if
they have anticipatory utility,

336
00:15:23,320 --> 00:15:27,640
that might affect the choice
of timing of certain outcomes.

337
00:15:27,640 --> 00:15:31,090
That is to say, if you have the
choice when you can experience

338
00:15:31,090 --> 00:15:36,190
a certain good, you might
want to delay that or not,

339
00:15:36,190 --> 00:15:39,040
depending on your
anticipatory utility.

340
00:15:39,040 --> 00:15:40,660
For example, if I
asked you, would you

341
00:15:40,660 --> 00:15:44,250
like to go on a vacation next
week or six months from now

342
00:15:44,250 --> 00:15:45,860
or six weeks from now?

343
00:15:45,860 --> 00:15:49,810
You might say, in fact,
six months from now

344
00:15:49,810 --> 00:15:52,090
is preferable
because then you'll

345
00:15:52,090 --> 00:15:55,270
have six months to look
forward to that experience

346
00:15:55,270 --> 00:15:57,040
and be really excited about it.

347
00:15:57,040 --> 00:15:58,880
Instead if I say, it's
only next week, well

348
00:15:58,880 --> 00:16:00,617
then, it might be
fun to go next week

349
00:16:00,617 --> 00:16:02,200
and maybe if you're
discounting, you'd

350
00:16:02,200 --> 00:16:04,760
rather it earlier than later.

351
00:16:04,760 --> 00:16:08,260
But then there's not very much
time to look forward to it

352
00:16:08,260 --> 00:16:12,700
and to savor and be excited
about this experience.

353
00:16:12,700 --> 00:16:15,760
So anticipatory utility
might affect the choice

354
00:16:15,760 --> 00:16:16,840
of timing of outcomes.

355
00:16:16,840 --> 00:16:19,780
We're going to talk
about this in a bit.

356
00:16:19,780 --> 00:16:23,890
Second, and perhaps
more consequentially,

357
00:16:23,890 --> 00:16:26,200
anticipatory utility
also may affect

358
00:16:26,200 --> 00:16:29,830
people's beliefs and their
information acquisition.

359
00:16:29,830 --> 00:16:31,540
That is to say, if
there is some things

360
00:16:31,540 --> 00:16:34,280
that I like to look forward
to in life-- for example,

361
00:16:34,280 --> 00:16:37,090
if I think I'm a healthy
person, I'm going to age really

362
00:16:37,090 --> 00:16:39,580
happily, and I'm going
to live until age 90

363
00:16:39,580 --> 00:16:46,010
happily, for a long time,
well then for example,

364
00:16:46,010 --> 00:16:48,340
that anticipatory
utility might then

365
00:16:48,340 --> 00:16:52,310
depend a lot on the beliefs
about my health status.

366
00:16:52,310 --> 00:16:54,610
And now if there were
tests or some information

367
00:16:54,610 --> 00:17:02,110
that I could acquire about
HIV, be it about cancer,

368
00:17:02,110 --> 00:17:04,300
be it about Huntington's
Disease and the like--

369
00:17:04,300 --> 00:17:08,150
it's very serious
potential diseases,

370
00:17:08,150 --> 00:17:14,390
people might under-use or
under-acquire such a type

371
00:17:14,390 --> 00:17:17,359
of information because
they want to maintain

372
00:17:17,359 --> 00:17:19,520
overly positive
beliefs about what's

373
00:17:19,520 --> 00:17:20,944
going to happen in the future.

374
00:17:20,944 --> 00:17:22,819
And that could be
potentially quite important

375
00:17:22,819 --> 00:17:25,790
because if people are not
getting, for example, cancer

376
00:17:25,790 --> 00:17:29,300
screening, well then some
treatments that perhaps could

377
00:17:29,300 --> 00:17:32,210
be done very early
might get delayed,

378
00:17:32,210 --> 00:17:34,490
and that could be
potentially quite costly.

379
00:17:34,490 --> 00:17:36,460
We're going to talk
about this second.

380
00:17:36,460 --> 00:17:36,960
OK.

381
00:17:36,960 --> 00:17:39,050
Let me show you some
motivating evidence

382
00:17:39,050 --> 00:17:41,130
of anticipatory utility.

383
00:17:41,130 --> 00:17:44,760
This is not so much to establish
the existence of such utility

384
00:17:44,760 --> 00:17:47,660
to you as like a very rigorous
test and showing exactly

385
00:17:47,660 --> 00:17:50,330
this is anticipatory utility
and how much of that is there,

386
00:17:50,330 --> 00:17:52,040
but rather to get
you to start thinking

387
00:17:52,040 --> 00:17:55,646
about the patterns of
behavior generated by it.

388
00:17:55,646 --> 00:17:58,010
So George Loewenstein
ingeniously

389
00:17:58,010 --> 00:18:01,340
asked undergrads about their
hypothetical willingness

390
00:18:01,340 --> 00:18:05,133
to pay now to obtain or
avoid certain experiences.

391
00:18:05,133 --> 00:18:06,800
So they asked them
about the willingness

392
00:18:06,800 --> 00:18:09,620
to pay as a function
of the amount of time

393
00:18:09,620 --> 00:18:12,120
until the experience occurs.

394
00:18:12,120 --> 00:18:14,510
So all values are normalized
relative to students'

395
00:18:14,510 --> 00:18:17,960
willingness to pay to obtain
the experience right away.

396
00:18:17,960 --> 00:18:19,910
So you ask people
about, like, how much

397
00:18:19,910 --> 00:18:23,880
are you going to pay for right
away and 24 hours from now

398
00:18:23,880 --> 00:18:26,900
and three days from now, and
a year from now, five years,

399
00:18:26,900 --> 00:18:28,340
10 years from now?

400
00:18:28,340 --> 00:18:31,820
And then the willingness
to pay right now

401
00:18:31,820 --> 00:18:36,740
is 1 by definition and
everything is relative to that.

402
00:18:36,740 --> 00:18:40,370
What are the experiences
that you ask people about?

403
00:18:40,370 --> 00:18:45,360
There's sort of both pleasant
and unpleasant experiences.

404
00:18:45,360 --> 00:18:47,360
One of them is
receiving monetary gain

405
00:18:47,360 --> 00:18:49,190
or avoiding monetary losses.

406
00:18:49,190 --> 00:18:50,780
There's obtaining
a kiss from a movie

407
00:18:50,780 --> 00:18:52,520
star of the student's choice.

408
00:18:52,520 --> 00:18:55,310
And there is avoiding a
non-lethal but very painful

409
00:18:55,310 --> 00:18:56,360
electric shock.

410
00:18:56,360 --> 00:18:58,880
And now you can think
about why Loewenstein

411
00:18:58,880 --> 00:19:01,010
asked about hypothetical
willingness to pay,

412
00:19:01,010 --> 00:19:05,870
because implementing that would
be pretty tough to actually do.

413
00:19:05,870 --> 00:19:10,530
Now when you think about
these types of experiences,

414
00:19:10,530 --> 00:19:12,030
you can think of
it about like, what

415
00:19:12,030 --> 00:19:14,700
would your hypothetical
willingness to pay be?

416
00:19:14,700 --> 00:19:18,480
And how would that look like
as a function of the timing?

417
00:19:18,480 --> 00:19:21,660
Would it go up or would
it go down over time?

418
00:19:21,660 --> 00:19:23,650
And there's going to
be two forces at play.

419
00:19:23,650 --> 00:19:25,390
There's going to be
discounting at play.

420
00:19:25,390 --> 00:19:28,920
And there's going to be
anticipatory utility at play.

421
00:19:28,920 --> 00:19:30,480
We talked about
discounting already

422
00:19:30,480 --> 00:19:32,430
a lot, which is,
people like to have

423
00:19:32,430 --> 00:19:34,830
positive stuff in the present--

424
00:19:34,830 --> 00:19:37,650
or rather in the present
than in the future.

425
00:19:37,650 --> 00:19:40,900
People like to push negative
stuff away to the future.

426
00:19:40,900 --> 00:19:43,740
So if bad stuff is going to
happen, like an electric shock,

427
00:19:43,740 --> 00:19:46,890
you'd rather have
that 10 years from now

428
00:19:46,890 --> 00:19:49,440
rather than right away.

429
00:19:49,440 --> 00:19:53,310
So then the question now is,
how does anticipatory utility

430
00:19:53,310 --> 00:19:56,430
affect those kinds of choices?

431
00:19:56,430 --> 00:20:02,080
And I already gave you some of
the situation to start with,

432
00:20:02,080 --> 00:20:07,410
which is like, if you had a
vacation that you potentially

433
00:20:07,410 --> 00:20:10,380
can experience, would you
rather have this right now?

434
00:20:10,380 --> 00:20:12,760
Would you rather have
it in a week from now,

435
00:20:12,760 --> 00:20:15,310
six months from now,
or 10 years from now?

436
00:20:15,310 --> 00:20:17,380
Well that depends on your
anticipatory utility.

437
00:20:17,380 --> 00:20:21,270
You might prefer to have
it in six months from now

438
00:20:21,270 --> 00:20:23,340
because that allows
you to look forward

439
00:20:23,340 --> 00:20:25,170
to it for quite a long time.

440
00:20:25,170 --> 00:20:27,780
You might not want to
have it 10 years from now.

441
00:20:27,780 --> 00:20:29,850
That might be good
from the perspective

442
00:20:29,850 --> 00:20:32,910
of anticipatory utility, but
it's really, really far away

443
00:20:32,910 --> 00:20:36,340
and you'd rather have things in
the present than in the future.

444
00:20:36,340 --> 00:20:39,570
So maybe if you take
together anticipatory utility

445
00:20:39,570 --> 00:20:44,670
and discounting, you'd rather
have it in an immediate amount

446
00:20:44,670 --> 00:20:47,880
of time from now, which
gives you the sort of a form

447
00:20:47,880 --> 00:20:53,000
of an inverse U-shape
of valuations over time,

448
00:20:53,000 --> 00:20:55,910
or valuations as a
function of when--

449
00:20:55,910 --> 00:20:57,500
right now of a
function of what's

450
00:20:57,500 --> 00:20:59,430
going to happen in the future.

451
00:20:59,430 --> 00:21:01,290
Let me show you what I mean.

452
00:21:01,290 --> 00:21:05,870
So when you look at
Loewenstein's examples--

453
00:21:05,870 --> 00:21:09,230
in particular, the
kiss of the movie star

454
00:21:09,230 --> 00:21:12,390
is an example of
an inverse U, where

455
00:21:12,390 --> 00:21:14,510
this is a pleasant experience.

456
00:21:14,510 --> 00:21:17,270
And what seems to be the
case is that some people

457
00:21:17,270 --> 00:21:24,290
prefer that experience to happen
in three hours, 24 hours, three

458
00:21:24,290 --> 00:21:28,310
days, and one year from now,
compared to immediately.

459
00:21:28,310 --> 00:21:30,470
You see the values
here are always

460
00:21:30,470 --> 00:21:34,098
higher than 1, which is sort of
what things are normalized to.

461
00:21:34,098 --> 00:21:35,390
So let me back up for a second.

462
00:21:35,390 --> 00:21:36,620
What does this graph show?

463
00:21:36,620 --> 00:21:40,160
It shows the time delay on the
x-axis, which is immediately,

464
00:21:40,160 --> 00:21:42,860
three hours, 24 hours, three
days, one year, 10 years

465
00:21:42,860 --> 00:21:44,430
from now on the x-axis.

466
00:21:44,430 --> 00:21:47,060
That's when the actual
experience is happening.

467
00:21:47,060 --> 00:21:48,950
And on the y-axis
is the proportion

468
00:21:48,950 --> 00:21:50,450
of the current value.

469
00:21:50,450 --> 00:21:55,340
And it's normalized to 1, so
the valuation immediately is 1.

470
00:21:55,340 --> 00:21:58,960
Notice that these are
willingness to pay

471
00:21:58,960 --> 00:22:02,910
to receive the experience or
willingness to pay to avoid it.

472
00:22:02,910 --> 00:22:05,240
So everything is positive.

473
00:22:05,240 --> 00:22:08,450
Now for the kiss now,
we see that the delay

474
00:22:08,450 --> 00:22:11,630
of three days from now seems
to have the highest valuation.

475
00:22:11,630 --> 00:22:15,480
So people like to
delay this for a bit.

476
00:22:15,480 --> 00:22:18,710
Notice that discounting would
not generate you this pattern.

477
00:22:18,710 --> 00:22:20,270
Discounting would
say, you want it

478
00:22:20,270 --> 00:22:24,140
right away because you
really enjoy this experience.

479
00:22:24,140 --> 00:22:27,180
So anticipatory utility would
say, well three days from now

480
00:22:27,180 --> 00:22:30,213
and even a year from now
it's better, because now you

481
00:22:30,213 --> 00:22:31,880
can savor it, really
look forward to it,

482
00:22:31,880 --> 00:22:35,230
be excited about it
when that's happening.

483
00:22:35,230 --> 00:22:37,050
However, 10 years
from now, people

484
00:22:37,050 --> 00:22:39,990
seem to like less than right
now, presumably because it's

485
00:22:39,990 --> 00:22:41,370
really, really far away.

486
00:22:41,370 --> 00:22:42,900
So A-- I guess
you're discounting

487
00:22:42,900 --> 00:22:47,040
that a lot and the experience
itself gets discounted a lot.

488
00:22:47,040 --> 00:22:50,040
B-- even the
anticipatory utility

489
00:22:50,040 --> 00:22:51,870
might only kick in
nine years from now

490
00:22:51,870 --> 00:22:55,140
because it's really
so far away that it's

491
00:22:55,140 --> 00:22:57,600
hard to think about this
because it's so far away.

492
00:22:57,600 --> 00:23:02,220
And you might even experience
anticipatory utility

493
00:23:02,220 --> 00:23:04,090
nine years from now.

494
00:23:04,090 --> 00:23:06,790
But you might discount that
as well because it's really

495
00:23:06,790 --> 00:23:07,910
far away in the future.

496
00:23:07,910 --> 00:23:10,593
So it seems like people
have some preference

497
00:23:10,593 --> 00:23:11,260
for the present.

498
00:23:11,260 --> 00:23:13,450
There is some
discounting going on.

499
00:23:13,450 --> 00:23:15,760
And there's sort of two
forces at play-- discounting

500
00:23:15,760 --> 00:23:18,400
versus anticipatory utility.

501
00:23:18,400 --> 00:23:24,040
Now in contrast, when you
look at the negative shock,

502
00:23:24,040 --> 00:23:28,940
here it seems to be
that people really

503
00:23:28,940 --> 00:23:33,830
seem to dislike having that
shock in 10 years or one year

504
00:23:33,830 --> 00:23:37,280
from now, compared to
having it right away.

505
00:23:37,280 --> 00:23:38,180
What's going on here?

506
00:23:38,180 --> 00:23:41,060
Well if you have the shock in
one year, 10 years from now,

507
00:23:41,060 --> 00:23:42,770
this is really an
unpleasant thing

508
00:23:42,770 --> 00:23:44,300
that hangs over your head.

509
00:23:44,300 --> 00:23:50,180
So what, instead, people want
is they'd rather sort of get it

510
00:23:50,180 --> 00:23:55,400
over with right away and not
have to think about it too much

511
00:23:55,400 --> 00:23:56,540
overall.

512
00:23:56,540 --> 00:24:06,970
Now and that's, again, sort of
the opposite of discounting.

513
00:24:06,970 --> 00:24:09,130
If you just had discounting,
what you would say

514
00:24:09,130 --> 00:24:12,548
is, well rather
I'm willing to pay

515
00:24:12,548 --> 00:24:13,840
to avoid it if it's right away.

516
00:24:13,840 --> 00:24:15,430
It's really
unpleasant right away.

517
00:24:15,430 --> 00:24:17,530
It's not so bad if
it's 10 years from now.

518
00:24:17,530 --> 00:24:20,800
So what discounting
would say is,

519
00:24:20,800 --> 00:24:22,210
the function should
be going down

520
00:24:22,210 --> 00:24:24,453
as you see it for losing $4.

521
00:24:24,453 --> 00:24:25,120
And why is that?

522
00:24:25,120 --> 00:24:28,000
Well losing $4 seems to
be like, people rather

523
00:24:28,000 --> 00:24:30,373
do that in the future
rather than in the present.

524
00:24:30,373 --> 00:24:32,540
And it's not really a thing
that you think about it.

525
00:24:32,540 --> 00:24:34,660
You don't have a lot
of anticipatory utility

526
00:24:34,660 --> 00:24:37,450
about losing $4 in
10 years from now.

527
00:24:37,450 --> 00:24:40,430
That's not such a
hugely important thing.

528
00:24:40,430 --> 00:24:43,150
However, if you get an electric
shock 10 years from now,

529
00:24:43,150 --> 00:24:45,230
that might be really unpleasant.

530
00:24:45,230 --> 00:24:48,160
So you really don't want to have
that in the year or 10 years

531
00:24:48,160 --> 00:24:50,890
from now, having this hang
over your head for a long time.

532
00:24:50,890 --> 00:24:53,440
So you'd rather
have it right away

533
00:24:53,440 --> 00:24:57,430
to not have to suffer from
any anticipatory utility, even

534
00:24:57,430 --> 00:24:59,680
though from a discounting
perspective, that's actually

535
00:24:59,680 --> 00:25:03,300
sort of worse.

536
00:25:03,300 --> 00:25:04,080
OK.

537
00:25:04,080 --> 00:25:07,200
And so I already said
all of this-- subjects

538
00:25:07,200 --> 00:25:12,420
prefer a kiss from a movie star
three days rather than now.

539
00:25:12,420 --> 00:25:14,910
They also prefer to
have a shock now rather

540
00:25:14,910 --> 00:25:17,830
than in one year or 10 years.

541
00:25:17,830 --> 00:25:21,430
Remember this is willingness
to pay to avoid a situation,

542
00:25:21,430 --> 00:25:24,900
so the willingness to pay
right now for the shock right

543
00:25:24,900 --> 00:25:26,880
now is lower than
the willingness

544
00:25:26,880 --> 00:25:29,290
to pay in one or 10 years.

545
00:25:29,290 --> 00:25:31,200
So the curve is going up.

546
00:25:31,200 --> 00:25:34,110
Now this contradicts
discounting of any kind.

547
00:25:34,110 --> 00:25:35,820
If you think about
any discounting,

548
00:25:35,820 --> 00:25:37,500
positive or negative
discounting--

549
00:25:37,500 --> 00:25:40,260
as in, you might have a
preference for the present

550
00:25:40,260 --> 00:25:41,980
or preference for the future--

551
00:25:41,980 --> 00:25:44,558
you cannot generate
these kinds of patterns.

552
00:25:44,558 --> 00:25:46,350
In particular, a pattern
that's really hard

553
00:25:46,350 --> 00:25:48,900
to generate is a
pattern where you

554
00:25:48,900 --> 00:25:51,180
get sort of these
hump-shaped cases

555
00:25:51,180 --> 00:25:54,760
where, essentially,
for inverse use,

556
00:25:54,760 --> 00:25:56,760
because either you want
something in the present

557
00:25:56,760 --> 00:26:00,360
or really far away
in the future.

558
00:26:00,360 --> 00:26:03,090
But as I said before, if you had
discounting, what you would get

559
00:26:03,090 --> 00:26:06,480
is essentially things are
either increasing or decreasing.

560
00:26:06,480 --> 00:26:09,960
In the time horizon, positive
things, you want right away.

561
00:26:09,960 --> 00:26:13,480
Negative things you'd
rather have in the future.

562
00:26:13,480 --> 00:26:17,470
And this is not at all
with Loewenstein finds.

563
00:26:17,470 --> 00:26:19,390
Now what is the
natural explanation?

564
00:26:19,390 --> 00:26:20,950
People look forward to the kiss.

565
00:26:20,950 --> 00:26:23,050
So they delay to
enjoy anticipation.

566
00:26:23,050 --> 00:26:25,610
And it's very unpleasant
to anticipate the shock,

567
00:26:25,610 --> 00:26:28,460
so they get it
over with quickly.

568
00:26:28,460 --> 00:26:31,107
Now why did Loewenstein
choose the kiss example?

569
00:26:31,107 --> 00:26:32,690
You can think about
this for a second.

570
00:26:38,300 --> 00:26:40,670
Well it is an experience
with a high degree

571
00:26:40,670 --> 00:26:44,060
of savorability-- something
you can think about and look

572
00:26:44,060 --> 00:26:46,570
forward to in the future.

573
00:26:46,570 --> 00:26:49,340
Loewenstein tries to rule
out alternative explanations

574
00:26:49,340 --> 00:26:50,750
based on preparation.

575
00:26:50,750 --> 00:26:55,040
You might sort of say, well
kissing a movie star right away

576
00:26:55,040 --> 00:27:01,400
might not be great because
you want to get ready, shower,

577
00:27:01,400 --> 00:27:03,800
sleep well, and tell all
your friends about it,

578
00:27:03,800 --> 00:27:10,220
and so on, or get some advice on
which movie star to pick and so

579
00:27:10,220 --> 00:27:10,880
on.

580
00:27:10,880 --> 00:27:13,422
So there might be some reason
that preparation might push you

581
00:27:13,422 --> 00:27:15,020
in three days from now.

582
00:27:15,020 --> 00:27:18,530
Similarly, if he had said a
dinner at a restaurant instead,

583
00:27:18,530 --> 00:27:21,170
you might say,
well in a few days'

584
00:27:21,170 --> 00:27:22,970
delay is perfectly
reasonable even

585
00:27:22,970 --> 00:27:24,860
without anticipatory utility.

586
00:27:24,860 --> 00:27:27,863
You might want to make
a time right away.

587
00:27:27,863 --> 00:27:29,030
It might not be a good time.

588
00:27:29,030 --> 00:27:31,113
You want to get a date,
et cetera, for the dinner.

589
00:27:31,113 --> 00:27:34,400
So choosing stuff later
because of preparation

590
00:27:34,400 --> 00:27:35,450
seems totally reasonable.

591
00:27:35,450 --> 00:27:39,500
That's not what Loewenstein
is talking about here.

592
00:27:39,500 --> 00:27:43,880
He really is thinking
about anticipatory utility.

593
00:27:43,880 --> 00:27:47,960
And so he has some
other examples,

594
00:27:47,960 --> 00:27:50,720
but really, you can argue
that really this is not

595
00:27:50,720 --> 00:27:55,130
about preparation,
but part of that

596
00:27:55,130 --> 00:27:56,790
could be preparation as well.

597
00:27:56,790 --> 00:27:58,748
But what you really think
about is going on is,

598
00:27:58,748 --> 00:28:01,640
really, this is about
anticipatory utility.

599
00:28:01,640 --> 00:28:03,260
When you think
about, is preparation

600
00:28:03,260 --> 00:28:06,410
problematic for the electric
shock in particular?

601
00:28:06,410 --> 00:28:08,090
Well the answer is
no, because that

602
00:28:08,090 --> 00:28:11,670
would induce subjects
to prefer it later,

603
00:28:11,670 --> 00:28:13,490
which is not what
Loewenstein finds.

604
00:28:13,490 --> 00:28:15,200
Remember, Loewenstein
finds that people

605
00:28:15,200 --> 00:28:17,990
would like to have the
shock right away, as opposed

606
00:28:17,990 --> 00:28:20,580
to a year or 10 years from now.

607
00:28:20,580 --> 00:28:22,370
And so preparation
would say, well, I

608
00:28:22,370 --> 00:28:26,400
want it in three days and
a year from now instead.

609
00:28:26,400 --> 00:28:29,870
But that's not really
what Loewenstein finds.

610
00:28:29,870 --> 00:28:32,060
So maybe if you're not
happy with the preparation

611
00:28:32,060 --> 00:28:35,060
explanation for the
kiss of the movie star,

612
00:28:35,060 --> 00:28:37,760
preparation will not be
able to explain to you

613
00:28:37,760 --> 00:28:41,310
the electric shock example.

614
00:28:41,310 --> 00:28:42,380
OK.

615
00:28:42,380 --> 00:28:43,380
There's another example.

616
00:28:43,380 --> 00:28:44,838
So Loewenstein has
this funny thing

617
00:28:44,838 --> 00:28:48,390
where he says, well
getting electric shock has

618
00:28:48,390 --> 00:28:50,270
been a little bit
of a weird example.

619
00:28:50,270 --> 00:28:52,080
So let me find something
more realistic.

620
00:28:52,080 --> 00:28:54,960
And then being an academic,
what he comes up with

621
00:28:54,960 --> 00:28:57,450
is cleaning hamster cages.

622
00:28:57,450 --> 00:29:01,260
So he asked subjects
how much they'd

623
00:29:01,260 --> 00:29:04,290
have to be paid to
clean 100 hamster cages.

624
00:29:04,290 --> 00:29:07,500
I've never cleaned any
hamster cages in my life.

625
00:29:07,500 --> 00:29:09,950
I imagine it'd be
quite unpleasant.

626
00:29:09,950 --> 00:29:11,700
So you think about,
what kinds of patterns

627
00:29:11,700 --> 00:29:13,552
do you expect to see?

628
00:29:13,552 --> 00:29:15,510
And what you expect to
see is sort of something

629
00:29:15,510 --> 00:29:17,430
similar to the electric shock.

630
00:29:17,430 --> 00:29:19,200
So people might really
not look forward

631
00:29:19,200 --> 00:29:22,325
to cleaning hamster
cages in a while from now

632
00:29:22,325 --> 00:29:23,700
and would rather
do it right away

633
00:29:23,700 --> 00:29:25,842
to avoid anticipatory utility.

634
00:29:25,842 --> 00:29:26,925
That would be the pattern.

635
00:29:30,860 --> 00:29:34,400
So that willingness
to pay for avoid it

636
00:29:34,400 --> 00:29:38,420
right away or you'd have
to pay them not so much

637
00:29:38,420 --> 00:29:39,980
do it right away,
compared to having

638
00:29:39,980 --> 00:29:43,250
to do it in a while from
now, because the anticipatory

639
00:29:43,250 --> 00:29:46,940
utility makes things worse, as
it did for the electric shock.

640
00:29:46,940 --> 00:29:50,750
And this is what
Loewenstein finds.

641
00:29:50,750 --> 00:29:52,520
If the payment is
now for cleaning

642
00:29:52,520 --> 00:29:56,720
to be performed next week,
it's going to be like $30.

643
00:29:56,720 --> 00:29:58,310
But if the payment
is now for cleaning

644
00:29:58,310 --> 00:30:00,590
to be performed in
a year from now,

645
00:30:00,590 --> 00:30:02,170
the payment has to be higher.

646
00:30:02,170 --> 00:30:03,980
It's $37.

647
00:30:03,980 --> 00:30:06,320
And again, discounting
preparation or the like

648
00:30:06,320 --> 00:30:10,860
would create the opposite--

649
00:30:10,860 --> 00:30:12,740
people would rather
have it in the future

650
00:30:12,740 --> 00:30:15,860
than in the present, which is
not what Loewenstein finds.

651
00:30:15,860 --> 00:30:22,080
Notice, again, these
are willingness to pay

652
00:30:22,080 --> 00:30:23,635
to have to do the experience.

653
00:30:23,635 --> 00:30:26,380
So how much would I have
to pay you to do it?

654
00:30:29,230 --> 00:30:32,320
Now again there's two
forces here at play--

655
00:30:32,320 --> 00:30:36,130
there is discounting
versus anticipation.

656
00:30:36,130 --> 00:30:38,030
Now how do we think
about discounting?

657
00:30:38,030 --> 00:30:40,510
So we talked about
discounting before.

658
00:30:40,510 --> 00:30:42,570
And there are sort
of three steps

659
00:30:42,570 --> 00:30:45,220
to thinking about discounting
that we talked about.

660
00:30:45,220 --> 00:30:46,840
One was, there was
a question like,

661
00:30:46,840 --> 00:30:49,630
what determines a person's
instantaneous utility

662
00:30:49,630 --> 00:30:51,142
at each point in time?

663
00:30:51,142 --> 00:30:53,600
We didn't talk about this very
much during time preference.

664
00:30:53,600 --> 00:30:55,990
We were just saying like,
here's an instantaneous utility

665
00:30:55,990 --> 00:30:58,990
function that determines how
happy you are at each point

666
00:30:58,990 --> 00:31:00,310
in time.

667
00:31:00,310 --> 00:31:02,080
What we talked a
lot about was, how

668
00:31:02,080 --> 00:31:06,170
do people integrate or aggregate
those utilities across time?

669
00:31:06,170 --> 00:31:08,570
So you have some utility
today, tomorrow, two days,

670
00:31:08,570 --> 00:31:09,640
three days from now.

671
00:31:09,640 --> 00:31:11,475
And we then talked
about, how do you

672
00:31:11,475 --> 00:31:12,850
aggregate, how
much weight do you

673
00:31:12,850 --> 00:31:14,882
put on the different periods?

674
00:31:14,882 --> 00:31:16,340
And then we talked
about, what does

675
00:31:16,340 --> 00:31:19,287
the person predict about the
future utility and behavior?

676
00:31:19,287 --> 00:31:21,370
Which is sort of the
question about sophistication

677
00:31:21,370 --> 00:31:25,610
and naivete that we
discussed as well.

678
00:31:25,610 --> 00:31:27,460
So as I said, the
discounting issues

679
00:31:27,460 --> 00:31:29,860
you covered are
about point number 2.

680
00:31:29,860 --> 00:31:32,050
The sophistication
versus naivete issues

681
00:31:32,050 --> 00:31:34,600
are more about point number 3.

682
00:31:34,600 --> 00:31:37,390
And here, people's prediction
about the future utility

683
00:31:37,390 --> 00:31:39,580
and behavior was only
relevant to the extent

684
00:31:39,580 --> 00:31:43,210
that it was helpful
or harmful in helping

685
00:31:43,210 --> 00:31:44,520
people make good decisions.

686
00:31:44,520 --> 00:31:45,020
Right?

687
00:31:45,020 --> 00:31:49,780
So people didn't derive utility
from being sophisticated

688
00:31:49,780 --> 00:31:53,170
or naive directly.

689
00:31:53,170 --> 00:31:56,320
People only derive utility from
their instantaneous utility

690
00:31:56,320 --> 00:31:59,020
function and from depending
on the weight they

691
00:31:59,020 --> 00:32:02,710
put on those different
instantaneous utilities.

692
00:32:02,710 --> 00:32:06,100
But their prediction
affected their choices,

693
00:32:06,100 --> 00:32:08,770
and their choices, in
turn, affected the utility.

694
00:32:08,770 --> 00:32:11,860
But it was never the case
that people's predictions,

695
00:32:11,860 --> 00:32:15,530
their beliefs directly
entered the utility function.

696
00:32:15,530 --> 00:32:18,760
So instead, anticipatory
utility is about point number 1.

697
00:32:18,760 --> 00:32:21,400
It's about the instantaneous
utility function-- what

698
00:32:21,400 --> 00:32:25,210
goes into that, and
perhaps people's beliefs

699
00:32:25,210 --> 00:32:26,950
about the future might do that.

700
00:32:26,950 --> 00:32:30,370
That's what we're
talking about now.

701
00:32:30,370 --> 00:32:33,820
Now notice that things
like social preferences

702
00:32:33,820 --> 00:32:37,180
or reference-dependent
preferences,

703
00:32:37,180 --> 00:32:39,210
those are also about number 1.

704
00:32:39,210 --> 00:32:41,730
Again, time preferences so
far that we talked about

705
00:32:41,730 --> 00:32:44,980
were about items number 2 and 3.

706
00:32:44,980 --> 00:32:47,890
Now what are the interactions
between anticipation

707
00:32:47,890 --> 00:32:49,380
and discounting?

708
00:32:49,380 --> 00:32:50,800
We talked about this already.

709
00:32:50,800 --> 00:32:55,330
So you can distinguish between
pleasant and unpleasant

710
00:32:55,330 --> 00:32:56,170
experiences.

711
00:32:56,170 --> 00:33:02,410
So anticipatory utility
is stronger for events

712
00:33:02,410 --> 00:33:03,790
that are closer in time, right?

713
00:33:03,790 --> 00:33:05,457
Something that's like
10 years from now,

714
00:33:05,457 --> 00:33:09,220
you're not that worried
about right now.

715
00:33:09,220 --> 00:33:12,200
For something that's tomorrow
or in two hours from now,

716
00:33:12,200 --> 00:33:13,870
you might be really
worried about.

717
00:33:13,870 --> 00:33:16,390
Now for pleasant and
savorable experiences,

718
00:33:16,390 --> 00:33:20,440
some delay is optimal to have
a few periods of anticipation.

719
00:33:20,440 --> 00:33:22,360
So think about
each hour, each day

720
00:33:22,360 --> 00:33:24,250
as a period of anticipation.

721
00:33:24,250 --> 00:33:28,360
So you'd rather have three
days than two days than one day

722
00:33:28,360 --> 00:33:31,720
of anticipation
because each day counts

723
00:33:31,720 --> 00:33:35,650
as the day of anticipation,
and you may value each day.

724
00:33:35,650 --> 00:33:38,500
But you don't want it to be too
far away because then there's

725
00:33:38,500 --> 00:33:39,490
also discounting.

726
00:33:39,490 --> 00:33:43,150
You'd rather have things at the
present or close to the present

727
00:33:43,150 --> 00:33:44,170
than in the future.

728
00:33:44,170 --> 00:33:47,153
You don't want stuff to be in
a year or two years from now

729
00:33:47,153 --> 00:33:48,820
because that's really
far away, and then

730
00:33:48,820 --> 00:33:50,740
you discount that
experience very much.

731
00:33:50,740 --> 00:33:52,510
Notice that you
might also discount

732
00:33:52,510 --> 00:33:54,810
the anticipatory utility.

733
00:33:54,810 --> 00:33:59,310
That is to say, suppose you have
only three days of anticipatory

734
00:33:59,310 --> 00:34:01,973
utility of a nice restaurant
or some nice experience.

735
00:34:01,973 --> 00:34:03,390
Only two or three
days before that

736
00:34:03,390 --> 00:34:08,070
experience you're going
to be excited about it.

737
00:34:08,070 --> 00:34:09,810
Well then if that's
in 10 years from now,

738
00:34:09,810 --> 00:34:11,540
you're going to
discount all of that.

739
00:34:11,540 --> 00:34:12,909
And then that's really far away.

740
00:34:12,909 --> 00:34:16,380
And if you really present
bias or just discount a lot,

741
00:34:16,380 --> 00:34:20,159
then you're also
going to discount

742
00:34:20,159 --> 00:34:21,630
the anticipatory utility.

743
00:34:21,630 --> 00:34:24,420
So there's some trade-off for
savorable, pleasant experiences

744
00:34:24,420 --> 00:34:27,480
between discounting and
anticipatory utility,

745
00:34:27,480 --> 00:34:33,159
which might give you this
inverse-U, hump shape power.

746
00:34:33,159 --> 00:34:36,580
Instead or in contrast,
for unpleasant, fearful

747
00:34:36,580 --> 00:34:39,219
experiences, you want to
either do it immediately

748
00:34:39,219 --> 00:34:40,944
to eliminate periods
of anticipation--

749
00:34:40,944 --> 00:34:42,940
so you might just say,
get it out of the way.

750
00:34:42,940 --> 00:34:45,580
I don't want any
anticipatory utility.

751
00:34:45,580 --> 00:34:48,070
And getting it out of the
way essentially minimizes

752
00:34:48,070 --> 00:34:52,300
anticipatory utility because
you get it over with.

753
00:34:52,300 --> 00:34:55,780
Or you might put it off as much
as possible for discounting

754
00:34:55,780 --> 00:34:57,400
reasons and to
weaken anticipation.

755
00:34:57,400 --> 00:34:59,890
That's to say, let's just
do it in 10 years from now.

756
00:34:59,890 --> 00:35:01,840
I might not worry about
it for quite a while.

757
00:35:01,840 --> 00:35:06,510
I might also just discount
any future anticipation.

758
00:35:06,510 --> 00:35:09,380
And for discounting, if
there's stuff in the future,

759
00:35:09,380 --> 00:35:11,480
I'd rather have bad stuff
happen in the future

760
00:35:11,480 --> 00:35:13,230
than in the present
because it essentially

761
00:35:13,230 --> 00:35:14,760
discounts the future.

762
00:35:14,760 --> 00:35:17,460
And it's good for me to
discount bad stuff that's

763
00:35:17,460 --> 00:35:20,690
happening in the future.

764
00:35:20,690 --> 00:35:22,750
So far we talked
about the implications

765
00:35:22,750 --> 00:35:25,620
of anticipatory utility for
the timing of consumption.

766
00:35:25,620 --> 00:35:26,120
Right?

767
00:35:26,120 --> 00:35:29,980
That is to say, when would
you like a certain experience

768
00:35:29,980 --> 00:35:31,720
to happen?

769
00:35:31,720 --> 00:35:36,530
In the immediate present, in
a few days, or further away

770
00:35:36,530 --> 00:35:37,480
in the future?

771
00:35:37,480 --> 00:35:40,810
But we took it as a given
that something might happen

772
00:35:40,810 --> 00:35:43,300
and then the question
was just when.

773
00:35:43,300 --> 00:35:46,990
You could think of some examples
where that might be important.

774
00:35:46,990 --> 00:35:51,790
Perhaps, more important overall
for people's welfare decisions,

775
00:35:51,790 --> 00:35:55,270
and perhaps also for policy is
people's information-gathering

776
00:35:55,270 --> 00:35:56,770
and beliefs.

777
00:35:56,770 --> 00:36:00,025
That is to say, you might get
a situation where anticipatory

778
00:36:00,025 --> 00:36:01,540
or ego utility--

779
00:36:01,540 --> 00:36:02,710
I'm going to show you--

780
00:36:02,710 --> 00:36:06,580
might affect how much
information people gather.

781
00:36:06,580 --> 00:36:07,990
And they might
not be as informed

782
00:36:07,990 --> 00:36:10,000
as they could be
otherwise because

783
00:36:10,000 --> 00:36:12,940
of those anticipatory
utility reasons.

784
00:36:12,940 --> 00:36:15,400
So one question you might
ask yourself is, well,

785
00:36:15,400 --> 00:36:17,890
would an individual in
a non-strategic setting

786
00:36:17,890 --> 00:36:21,790
with no anticipatory
utility ever strictly prefer

787
00:36:21,790 --> 00:36:24,130
to refuse free information?

788
00:36:24,130 --> 00:36:27,310
And it's actually hard to
come up with some situations

789
00:36:27,310 --> 00:36:29,680
where people just would
refuse information if they're

790
00:36:29,680 --> 00:36:31,360
perfectly neoclassical.

791
00:36:31,360 --> 00:36:33,425
You might say, well people
might be overwhelmed.

792
00:36:33,425 --> 00:36:35,050
There's too much
information available.

793
00:36:35,050 --> 00:36:38,320
And you might not be able
to attend to everything.

794
00:36:38,320 --> 00:36:41,050
But in general, I think
the assumption in economics

795
00:36:41,050 --> 00:36:44,450
is, well the information
could be useful for something.

796
00:36:44,450 --> 00:36:46,090
You might not even
know that right now,

797
00:36:46,090 --> 00:36:47,757
but it might turn out
that actually it's

798
00:36:47,757 --> 00:36:49,660
quite interesting information.

799
00:36:49,660 --> 00:36:51,640
And in particular,
usually, the assumption

800
00:36:51,640 --> 00:36:53,470
is there's free disposal.

801
00:36:53,470 --> 00:36:54,070
Right?

802
00:36:54,070 --> 00:36:56,260
If the information is not
useful, just forget about it.

803
00:36:56,260 --> 00:36:56,830
Don't care about it.

804
00:36:56,830 --> 00:36:57,330
Whatever.

805
00:36:57,330 --> 00:36:59,650
Just write it down
somewhere and whatever.

806
00:36:59,650 --> 00:37:01,500
It might be important
in the future.

807
00:37:01,500 --> 00:37:04,270
But really, why bother
whether or not to have it?

808
00:37:04,270 --> 00:37:05,230
It's no problem.

809
00:37:05,230 --> 00:37:09,560
So you would never
refuse it directly.

810
00:37:09,560 --> 00:37:12,230
You might not pay for it
if you think it's useless,

811
00:37:12,230 --> 00:37:17,970
but you would never refuse
to actually get it for free.

812
00:37:17,970 --> 00:37:21,750
In contrast, somebody with
anticipatory feeling cannot

813
00:37:21,750 --> 00:37:25,050
ignore information because that
information affects his or her

814
00:37:25,050 --> 00:37:25,913
emotions.

815
00:37:25,913 --> 00:37:28,080
But if it's something that
some piece of information

816
00:37:28,080 --> 00:37:31,320
makes you really unhappy,
well it's very hard, actually,

817
00:37:31,320 --> 00:37:34,800
to forget about it and ignore
it because once it's out there,

818
00:37:34,800 --> 00:37:37,650
once you've heard it, it's
really that you can't unhear it

819
00:37:37,650 --> 00:37:39,210
and it's very hard to forget.

820
00:37:39,210 --> 00:37:41,190
In particular, it's
hard to forget stuff

821
00:37:41,190 --> 00:37:43,320
that you really care
about, that you're

822
00:37:43,320 --> 00:37:44,910
upset about or anxious about.

823
00:37:44,910 --> 00:37:48,340
And so it's really hard to do.

824
00:37:48,340 --> 00:37:52,530
And so one quite
interesting example

825
00:37:52,530 --> 00:37:55,140
is Dr. House and Thirteen.

826
00:37:55,140 --> 00:37:58,490
Thirteen is one
of his employees.

827
00:37:58,490 --> 00:38:00,450
She's called Thirteen
because I think

828
00:38:00,450 --> 00:38:06,440
he had 25 or something interns.

829
00:38:06,440 --> 00:38:09,440
And I think he fired
almost all of them

830
00:38:09,440 --> 00:38:12,710
except for Thirteen who was
number 13 of these interns.

831
00:38:12,710 --> 00:38:14,450
He never-- at the
beginning, at least--

832
00:38:14,450 --> 00:38:16,062
bothered to learn
people's names.

833
00:38:16,062 --> 00:38:17,270
So he just gave them numbers.

834
00:38:17,270 --> 00:38:19,530
So Thirteen was number 13.

835
00:38:19,530 --> 00:38:22,000
She was an excellent doctor.

836
00:38:22,000 --> 00:38:24,610
It turns out that her
family had a history

837
00:38:24,610 --> 00:38:27,310
of Huntington's disease.

838
00:38:27,310 --> 00:38:34,210
And Thirteen had the prime
example, in the show,

839
00:38:34,210 --> 00:38:36,010
of information avoidance.

840
00:38:36,010 --> 00:38:39,840
She did not want to learn about
whether she had the disease

841
00:38:39,840 --> 00:38:40,340
or not.

842
00:38:40,340 --> 00:38:42,640
And so the Huntington's
Disease is such

843
00:38:42,640 --> 00:38:45,820
that, if your parents have
the disease, your probability

844
00:38:45,820 --> 00:38:48,700
of having the disease
yourself is way higher than

845
00:38:48,700 --> 00:38:49,810
in the general population.

846
00:38:49,810 --> 00:38:56,060
It's about 50% overall if one of
your parents have the disease.

847
00:38:56,060 --> 00:38:58,930
And so then you might think it's
quite valuable to learn about

848
00:38:58,930 --> 00:39:01,960
whether you have disease or
not, for a variety of decisions

849
00:39:01,960 --> 00:39:04,360
that you might make in the
future or that are relevant

850
00:39:04,360 --> 00:39:07,780
for the future, ranging
from when to retire,

851
00:39:07,780 --> 00:39:10,210
how much to exercise,
what education

852
00:39:10,210 --> 00:39:12,700
to get, how much to save,
whether you have children

853
00:39:12,700 --> 00:39:15,220
or not.

854
00:39:15,220 --> 00:39:18,940
And Dr. House was usually
pretty irrational.

855
00:39:18,940 --> 00:39:21,610
And there is
choices or decisions

856
00:39:21,610 --> 00:39:26,830
that he does, was in fact
being very neoclassical here

857
00:39:26,830 --> 00:39:28,690
and saying, you should
get this information

858
00:39:28,690 --> 00:39:30,820
because it would be
very helpful for you.

859
00:39:30,820 --> 00:39:32,470
He, in fact, went
behind her back,

860
00:39:32,470 --> 00:39:35,680
tested her, and sent
her the results.

861
00:39:35,680 --> 00:39:39,370
And but then, Thirteen, for
at least for quite a while,

862
00:39:39,370 --> 00:39:41,290
did not go to look
at these results,

863
00:39:41,290 --> 00:39:44,800
presumably because she wanted
to make herself think that she

864
00:39:44,800 --> 00:39:48,520
will be healthy and sort of
delude herself in some ways

865
00:39:48,520 --> 00:39:51,790
about being a healthy person
and not having this disease,

866
00:39:51,790 --> 00:39:53,950
even though she was not sure.

867
00:39:53,950 --> 00:39:58,120
And so avoiding that
information helps

868
00:39:58,120 --> 00:39:59,950
you do that because
once you're tested,

869
00:39:59,950 --> 00:40:01,970
you're either
positive or negative.

870
00:40:01,970 --> 00:40:04,512
And it's very hard to
ignore that information

871
00:40:04,512 --> 00:40:05,470
once you have taken it.

872
00:40:05,470 --> 00:40:06,970
But before you have
been tested, you

873
00:40:06,970 --> 00:40:08,560
could always sort
of delude yourself

874
00:40:08,560 --> 00:40:13,500
and make yourself think that
you don't have the disease.

875
00:40:13,500 --> 00:40:15,560
Now what is
Huntington's Disease?

876
00:40:15,560 --> 00:40:17,840
Let me be a little
bit more specific.

877
00:40:17,840 --> 00:40:23,030
It's a degenerative
neurological disorder.

878
00:40:23,030 --> 00:40:27,350
It's a very severe and
heartbreaking disease.

879
00:40:27,350 --> 00:40:31,930
Essentially, it
affects the brain.

880
00:40:31,930 --> 00:40:35,660
It sets on around age
40 and really makes

881
00:40:35,660 --> 00:40:38,060
people very dysfunctional.

882
00:40:38,060 --> 00:40:40,460
And life expectancy is
around 60 for somebody

883
00:40:40,460 --> 00:40:42,980
with Huntington's
Disease compared to 80

884
00:40:42,980 --> 00:40:44,630
or even higher for
people who don't

885
00:40:44,630 --> 00:40:47,270
have Huntington's Disease.

886
00:40:47,270 --> 00:40:50,450
People with parents or a parent
with Huntington's Disease

887
00:40:50,450 --> 00:40:53,270
have about a 50% chance of
developing Huntington's Disease

888
00:40:53,270 --> 00:40:55,740
themselves.

889
00:40:55,740 --> 00:40:59,390
Since the 1990s, there's a
genetic blood test available.

890
00:40:59,390 --> 00:41:02,510
And so you can provide at-risk
individuals with certainty

891
00:41:02,510 --> 00:41:04,830
about whether will
develop it so you

892
00:41:04,830 --> 00:41:08,420
know for sure either you will
develop it or you will not.

893
00:41:08,420 --> 00:41:12,890
And those lab tests
cost about $200 to $300,

894
00:41:12,890 --> 00:41:16,493
plus consulting and other costs.

895
00:41:16,493 --> 00:41:18,410
The tests here are often
covered by insurance,

896
00:41:18,410 --> 00:41:21,350
but most tests are
paid out of pocket.

897
00:41:21,350 --> 00:41:25,200
Emily Oster and co-authors
of the paper that

898
00:41:25,200 --> 00:41:27,480
is on the reading
list were arguing

899
00:41:27,480 --> 00:41:29,880
that people were not doing
that partially to keep

900
00:41:29,880 --> 00:41:33,780
the test results private.

901
00:41:33,780 --> 00:41:36,750
Importantly, there's no cure
or nothing that we can actually

902
00:41:36,750 --> 00:41:39,410
do to improve the disease.

903
00:41:39,410 --> 00:41:41,910
So when you think about other
diseases, such as HIV or other

904
00:41:41,910 --> 00:41:46,020
like, usually there,
there's a key motivation

905
00:41:46,020 --> 00:41:50,550
to learn about whether somebody
is positive or negative,

906
00:41:50,550 --> 00:41:54,000
because then they can get
antiretroviral treatment

907
00:41:54,000 --> 00:41:54,840
or the like.

908
00:41:54,840 --> 00:41:56,560
Here that's not the case.

909
00:41:56,560 --> 00:41:59,350
So there's no actual
cure or behaviors

910
00:41:59,350 --> 00:42:03,270
that you could do to
that could mitigate

911
00:42:03,270 --> 00:42:05,260
the course of the disease.

912
00:42:05,260 --> 00:42:07,320
However, there's other
potential behaviors

913
00:42:07,320 --> 00:42:08,520
that you could engage in--

914
00:42:08,520 --> 00:42:13,230
so prepare you better and
deal better with the disease

915
00:42:13,230 --> 00:42:15,490
once it sets on.

916
00:42:15,490 --> 00:42:18,390
So what are these reasons?

917
00:42:18,390 --> 00:42:20,350
Why could such a
test be valuable?

918
00:42:20,350 --> 00:42:23,130
Think about this for a second.

919
00:42:23,130 --> 00:42:25,890
There's a number of
potential reasons

920
00:42:25,890 --> 00:42:27,630
that you might think about.

921
00:42:27,630 --> 00:42:28,830
I've listed a few.

922
00:42:28,830 --> 00:42:30,570
There's a question
about whether or not

923
00:42:30,570 --> 00:42:32,160
you want to have a child.

924
00:42:32,160 --> 00:42:35,160
There's issues about marriage.

925
00:42:35,160 --> 00:42:38,500
Would you like to get
married or find a partner?

926
00:42:38,500 --> 00:42:40,000
Or do you want to
tell your partner?

927
00:42:40,000 --> 00:42:40,950
And so on.

928
00:42:40,950 --> 00:42:43,410
There's questions
about retirement.

929
00:42:43,410 --> 00:42:45,700
When do you want to retire?

930
00:42:45,700 --> 00:42:48,690
For example, if you wanted to
travel a lot after retirement.

931
00:42:48,690 --> 00:42:52,140
Well if the disease
sets on at age 40,

932
00:42:52,140 --> 00:42:54,510
you might want to do
that a lot earlier.

933
00:42:54,510 --> 00:42:57,690
Education-- usually we think
that the returns to education

934
00:42:57,690 --> 00:42:59,530
are high.

935
00:42:59,530 --> 00:43:01,710
So it's good news for
anybody who is studying.

936
00:43:01,710 --> 00:43:03,780
But usually these
returns are accrued

937
00:43:03,780 --> 00:43:05,760
over a long period of time.

938
00:43:05,760 --> 00:43:09,480
You're done with your
education at the age 22 or 25.

939
00:43:09,480 --> 00:43:15,660
You can then start working
from age 25 to age 65

940
00:43:15,660 --> 00:43:17,340
or the like or even longer.

941
00:43:17,340 --> 00:43:19,403
And so that's a long time.

942
00:43:19,403 --> 00:43:21,320
But if instead, you have
Huntington's Disease,

943
00:43:21,320 --> 00:43:24,470
you might only have until
age 40 or 45 or the like.

944
00:43:24,470 --> 00:43:28,080
So the returns to
education are way lower.

945
00:43:28,080 --> 00:43:30,440
You might also do things
like participation

946
00:43:30,440 --> 00:43:31,710
in clinical research.

947
00:43:31,710 --> 00:43:34,010
Perhaps there's some
chance that at some point

948
00:43:34,010 --> 00:43:35,030
there might be a cure.

949
00:43:35,030 --> 00:43:37,050
You maybe want to
contribute to that.

950
00:43:37,050 --> 00:43:40,660
So there's lots of potential
benefits of knowing,

951
00:43:40,660 --> 00:43:44,090
and that test could really be
extremely valuable for you.

952
00:43:44,090 --> 00:43:49,820
And surely the value could
be higher than $200 or $300.

953
00:43:49,820 --> 00:43:52,970
Now what of the
paper by Oster et al?

954
00:43:52,970 --> 00:43:55,850
So Oster et al. observe
a sample of previously

955
00:43:55,850 --> 00:44:01,350
untested at-risk individuals
over the course of 10 years.

956
00:44:01,350 --> 00:44:06,500
Why is it useful to have a
sample of at-risk individuals?

957
00:44:06,500 --> 00:44:08,720
Well because the
base rate, the rate

958
00:44:08,720 --> 00:44:10,550
of people who are
not at risk, who

959
00:44:10,550 --> 00:44:13,580
don't have any parents
with Huntington's Disease,

960
00:44:13,580 --> 00:44:16,740
that rate is quite low.

961
00:44:16,740 --> 00:44:18,870
So not being tested is
not so much a puzzle.

962
00:44:18,870 --> 00:44:21,370
If your chance is like
0.00-something percent,

963
00:44:21,370 --> 00:44:25,260
then it's really not that--
it's quite costly to do.

964
00:44:25,260 --> 00:44:28,690
It's $200, $300, plus
hassle cost and so on.

965
00:44:28,690 --> 00:44:30,480
And there's many
diseases one could have.

966
00:44:30,480 --> 00:44:31,740
Why test for Huntington's?

967
00:44:31,740 --> 00:44:34,080
It's perfectly reasonable
to not test for it.

968
00:44:34,080 --> 00:44:37,560
But here, there are people,
these at-risk people,

969
00:44:37,560 --> 00:44:43,818
their chance is
50% to start with.

970
00:44:43,818 --> 00:44:45,110
So there's a lot to learn from.

971
00:44:45,110 --> 00:44:49,470
You go from 50% to either 0% of
having it or 100% of having it.

972
00:44:49,470 --> 00:44:53,180
So there's huge changes in
your beliefs, potentially.

973
00:44:53,180 --> 00:44:57,350
While if you are a person
who is not at risk,

974
00:44:57,350 --> 00:45:01,130
your chance of getting
it to start with is like

975
00:45:01,130 --> 00:45:04,910
0.00-something percent, with
very high chance you're going

976
00:45:04,910 --> 00:45:05,990
to go to zero from that.

977
00:45:05,990 --> 00:45:08,360
So that's almost no
change at all anyway.

978
00:45:08,360 --> 00:45:10,080
And there's only like
a tiny, tiny chance

979
00:45:10,080 --> 00:45:12,665
that you're actually
positive, in which, of course,

980
00:45:12,665 --> 00:45:14,790
you might want to change
your behavior quite a bit.

981
00:45:14,790 --> 00:45:16,540
But the weight on that
should be quite low

982
00:45:16,540 --> 00:45:20,570
because the probability of a
positive test is really low.

983
00:45:20,570 --> 00:45:27,410
So Oster et al find very low
rates of this genetic testing.

984
00:45:27,410 --> 00:45:30,410
Fewer than 10% of individuals
pursue predictive testing

985
00:45:30,410 --> 00:45:34,220
during the studies, over
this long period of time.

986
00:45:34,220 --> 00:45:37,310
Many individuals get tested
to confirm the disease rather

987
00:45:37,310 --> 00:45:40,590
than actually learning about
whether they have it or not.

988
00:45:40,590 --> 00:45:44,810
You might think, what's really
important is for the reasons

989
00:45:44,810 --> 00:45:47,070
that I mentioned here--

990
00:45:47,070 --> 00:45:48,990
it's generating knowledge.

991
00:45:48,990 --> 00:45:53,460
Right, you want to know,
should you retire early or not?

992
00:45:53,460 --> 00:45:55,080
For that, you want knowledge.

993
00:45:55,080 --> 00:45:57,580
You want to reveal uncertainty.

994
00:45:57,580 --> 00:45:59,850
So if your chance to have
the disease to start with

995
00:45:59,850 --> 00:46:04,170
is 50%, going from 50%
to 0% or 50% to 100%,

996
00:46:04,170 --> 00:46:09,210
that's huge potential
knowledge that's being created.

997
00:46:09,210 --> 00:46:13,230
Once you think the
chances like 99% or 99.9%,

998
00:46:13,230 --> 00:46:16,360
going from 99% to 100%, you
actually don't learn that much.

999
00:46:16,360 --> 00:46:18,450
And you shouldn't change
your behavior very much

1000
00:46:18,450 --> 00:46:21,345
from confirming that
you have the disease.

1001
00:46:21,345 --> 00:46:23,220
Similarly, actually,
there's similar evidence

1002
00:46:23,220 --> 00:46:25,020
in studies on HIV,
breast cancer,

1003
00:46:25,020 --> 00:46:26,460
and other types of testing.

1004
00:46:26,460 --> 00:46:29,760
People tend to
systematically under-test

1005
00:46:29,760 --> 00:46:33,480
even if the chance of having
certain diseases is quite high.

1006
00:46:33,480 --> 00:46:36,150
And what's somewhat different
for HIV and cancer--

1007
00:46:36,150 --> 00:46:39,720
any cancer, particularly
breast cancer testing,

1008
00:46:39,720 --> 00:46:44,340
there's at least some hope
that if a disease gets

1009
00:46:44,340 --> 00:46:46,740
detected early,
one can potentially

1010
00:46:46,740 --> 00:46:48,120
do something about it.

1011
00:46:48,120 --> 00:46:53,610
There's some recent
controversies or discussions

1012
00:46:53,610 --> 00:46:56,323
on like, is cancer
testing actually helpful?

1013
00:46:56,323 --> 00:46:58,740
And are we over-testing in the
sense, is the test actually

1014
00:46:58,740 --> 00:47:02,190
helpful in detecting
potential diseases?

1015
00:47:02,190 --> 00:47:04,560
But surely for HIV, it
would be quite valuable

1016
00:47:04,560 --> 00:47:06,930
if you knew early on
whether you have a disease

1017
00:47:06,930 --> 00:47:08,730
or not because then
you could essentially

1018
00:47:08,730 --> 00:47:13,910
take ARV, antiretroviral
treatment, to help you.

1019
00:47:13,910 --> 00:47:18,450
Now let me show you first
who's getting tested.

1020
00:47:18,450 --> 00:47:22,970
So what you see on this graph
is on the x-axis investigator

1021
00:47:22,970 --> 00:47:26,240
evaluation of symptoms
at the last visit.

1022
00:47:26,240 --> 00:47:28,985
So on the left, these are
people who are normal,

1023
00:47:28,985 --> 00:47:30,380
who don't show any symptoms.

1024
00:47:30,380 --> 00:47:32,270
On the right, people
have like certain signs

1025
00:47:32,270 --> 00:47:33,270
of Huntington's Disease.

1026
00:47:33,270 --> 00:47:35,240
And everything else
in between, this

1027
00:47:35,240 --> 00:47:37,680
is sort of in the
middle of that.

1028
00:47:37,680 --> 00:47:41,870
So further to the right means
people have more symptoms.

1029
00:47:41,870 --> 00:47:43,798
In particular, to
the very right,

1030
00:47:43,798 --> 00:47:45,590
these are people have
like certain symptoms

1031
00:47:45,590 --> 00:47:47,060
of Huntington's Disease.

1032
00:47:47,060 --> 00:47:49,100
And what we see
is, on the y-axis,

1033
00:47:49,100 --> 00:47:51,230
whether people since
their last visit

1034
00:47:51,230 --> 00:47:54,380
get tested-- so there are
several visits over time.

1035
00:47:54,380 --> 00:48:00,350
And the raw means are what
I wanted you to focus on.

1036
00:48:00,350 --> 00:48:03,920
This is the upper
of those two lines.

1037
00:48:03,920 --> 00:48:06,340
And what we see is
essentially that testing rates

1038
00:48:06,340 --> 00:48:08,590
are very, very low.

1039
00:48:08,590 --> 00:48:13,240
The largest are about 5%
in this particular sample.

1040
00:48:13,240 --> 00:48:17,350
And that's essentially
increasing in the symptoms

1041
00:48:17,350 --> 00:48:18,310
that people have.

1042
00:48:18,310 --> 00:48:20,800
So overall that
fraction is high.

1043
00:48:20,800 --> 00:48:22,330
And in particular
for people where

1044
00:48:22,330 --> 00:48:25,810
you think the value of testing
would be quite high, these are

1045
00:48:25,810 --> 00:48:28,810
people who don't necessarily
show any symptoms

1046
00:48:28,810 --> 00:48:32,260
and people who have some
symptoms but not very

1047
00:48:32,260 --> 00:48:34,210
strong symptoms, you
would think for them

1048
00:48:34,210 --> 00:48:37,150
it would be particularly
helpful to get tested

1049
00:48:37,150 --> 00:48:40,160
because you could learn a lot.

1050
00:48:40,160 --> 00:48:42,160
But instead, those are,
in fact, the people

1051
00:48:42,160 --> 00:48:43,630
who almost don't test at all.

1052
00:48:43,630 --> 00:48:46,920
The test rates are
something like 1% to 3%.

1053
00:48:46,920 --> 00:48:52,150
Now as I said before, for
people with certain signs

1054
00:48:52,150 --> 00:48:54,150
of Huntington's Disease,
the objective knowledge

1055
00:48:54,150 --> 00:48:56,150
from the test is very low
since there's no cure.

1056
00:48:59,250 --> 00:49:01,720
You're almost sure that you
have it anyway, so in a way,

1057
00:49:01,720 --> 00:49:03,550
you just really don't
learn very much.

1058
00:49:03,550 --> 00:49:06,050
If you have these certain signs
of Huntington's Disease plus

1059
00:49:06,050 --> 00:49:09,000
you're genetically predisposed
to have the disease,

1060
00:49:09,000 --> 00:49:12,600
the chance of actually having
disease is almost one anyway.

1061
00:49:12,600 --> 00:49:15,550
So the test really does not
give you a lot of information.

1062
00:49:15,550 --> 00:49:18,990
However, perhaps, it
changes your utilities

1063
00:49:18,990 --> 00:49:22,870
from beliefs, which I'm
going to talk about in a bit.

1064
00:49:22,870 --> 00:49:24,750
Notice that the
perceived probabilities

1065
00:49:24,750 --> 00:49:27,090
of having the disease might
be lower even for people

1066
00:49:27,090 --> 00:49:28,540
with certain symptoms.

1067
00:49:28,540 --> 00:49:32,250
So what I'm showing you here
is the investigator evaluation.

1068
00:49:32,250 --> 00:49:35,910
This is essentially a doctor
or neurologist actually looking

1069
00:49:35,910 --> 00:49:38,640
at the symptoms and
looking at, objectively,

1070
00:49:38,640 --> 00:49:40,530
what's your chance of
having the disease.

1071
00:49:40,530 --> 00:49:42,840
That's different from
what people actually

1072
00:49:42,840 --> 00:49:44,213
think they have.

1073
00:49:44,213 --> 00:49:45,630
So I guess A-- and
what we learned

1074
00:49:45,630 --> 00:49:50,630
here-- is the testing
rates are quite low.

1075
00:49:50,630 --> 00:49:54,900
Second, people
systematically under-predict

1076
00:49:54,900 --> 00:49:58,843
or are overoptimistic
about not having a disease.

1077
00:49:58,843 --> 00:50:00,260
That is what I'm
showing you here,

1078
00:50:00,260 --> 00:50:02,120
is a motor score,
which essentially

1079
00:50:02,120 --> 00:50:05,488
is an assessment of how
good are your motor skills.

1080
00:50:05,488 --> 00:50:07,655
And one unfortunate thing
about Huntington's Disease

1081
00:50:07,655 --> 00:50:10,490
is that your motor skills
are deteriorating a lot.

1082
00:50:10,490 --> 00:50:15,610
And so a high score
means here, essentially--

1083
00:50:15,610 --> 00:50:18,980
if it's bad means essentially
you're not doing well

1084
00:50:18,980 --> 00:50:22,020
and you're more likely to
have Huntington's Disease.

1085
00:50:22,020 --> 00:50:24,890
And what you see in the
upper limit on the y-axis,

1086
00:50:24,890 --> 00:50:27,080
is essentially the
probability-- the objective

1087
00:50:27,080 --> 00:50:30,690
and subjective probabilities--
of having the disease.

1088
00:50:30,690 --> 00:50:33,420
The upper line here
that you see at the top,

1089
00:50:33,420 --> 00:50:36,980
that line is the actual
probability, the estimated

1090
00:50:36,980 --> 00:50:38,300
actual probability.

1091
00:50:38,300 --> 00:50:42,500
And you see that's essentially
increasing in the motor scores.

1092
00:50:42,500 --> 00:50:46,200
So people who have almost
no symptoms overall,

1093
00:50:46,200 --> 00:50:49,160
they have essentially a 50%
chance of having the disease.

1094
00:50:49,160 --> 00:50:50,793
That's the risk to start with.

1095
00:50:50,793 --> 00:50:52,460
But then once people
have more symptoms,

1096
00:50:52,460 --> 00:50:54,080
that chance increases.

1097
00:50:54,080 --> 00:50:57,140
And once you have a motor
score in the 20s or 30s,

1098
00:50:57,140 --> 00:50:59,840
your objective probability
of having the disease

1099
00:50:59,840 --> 00:51:02,010
is close to 1.

1100
00:51:02,010 --> 00:51:04,440
Now in contrast, the second
line that you see here

1101
00:51:04,440 --> 00:51:07,770
in the middle, that is
the people's perceived

1102
00:51:07,770 --> 00:51:08,820
probabilities.

1103
00:51:08,820 --> 00:51:13,050
Those perceived probabilities
are vastly lower and far less

1104
00:51:13,050 --> 00:51:15,400
steep than the
actual probabilities.

1105
00:51:15,400 --> 00:51:17,790
You see that people's
perceived probabilities when

1106
00:51:17,790 --> 00:51:21,000
they have no symptoms are
still actually reasonably high,

1107
00:51:21,000 --> 00:51:22,980
and they're pretty
close to the truth.

1108
00:51:22,980 --> 00:51:27,720
They're about 40%, compared to
like something like 50%, 55%.

1109
00:51:27,720 --> 00:51:29,370
So that's actually
not that far off,

1110
00:51:29,370 --> 00:51:31,290
perhaps because it's very clear.

1111
00:51:31,290 --> 00:51:33,313
If you have a parent
who has the disease,

1112
00:51:33,313 --> 00:51:35,730
everybody knows essentially,
and particularly in this kind

1113
00:51:35,730 --> 00:51:39,000
of study, everybody knows
that the probability of having

1114
00:51:39,000 --> 00:51:41,932
the disease is high, and so that
perhaps, people can't really

1115
00:51:41,932 --> 00:51:43,890
lie to themselves and
know that the chances are

1116
00:51:43,890 --> 00:51:46,230
pretty high if they
have been untested.

1117
00:51:46,230 --> 00:51:48,660
But then people seem to
be largely in denial when

1118
00:51:48,660 --> 00:51:50,100
it comes to these symptoms.

1119
00:51:50,100 --> 00:51:52,770
People have these
symptoms, and when

1120
00:51:52,770 --> 00:51:57,540
you have scores of 20 to 30,
their perceived probability

1121
00:51:57,540 --> 00:52:00,070
of having the disease is
really only slightly higher.

1122
00:52:00,070 --> 00:52:01,760
It's about 50% or the like.

1123
00:52:01,760 --> 00:52:03,510
And so the people who
are about here, well

1124
00:52:03,510 --> 00:52:05,520
their actual probability
is much higher.

1125
00:52:05,520 --> 00:52:08,280
And people don't seem to
update information that's

1126
00:52:08,280 --> 00:52:11,070
really unfavorable
toward them in terms

1127
00:52:11,070 --> 00:52:14,700
of anticipatory utility
because they seem

1128
00:52:14,700 --> 00:52:17,260
to be feeling bad about it.

1129
00:52:17,260 --> 00:52:20,460
Notice that there's actually
a significant share of people

1130
00:52:20,460 --> 00:52:24,423
who persist and really
thinks about our reports

1131
00:52:24,423 --> 00:52:26,590
saying that there's no
chance of having the disease.

1132
00:52:26,590 --> 00:52:31,380
So there are some people who
have a motor score of 20 to 30,

1133
00:52:31,380 --> 00:52:34,845
and 10% to 20% of
people here seem to say,

1134
00:52:34,845 --> 00:52:36,930
I have a 0 chance of
Huntington's Disease, which

1135
00:52:36,930 --> 00:52:41,190
really seems to be unfortunately
delusional in some ways.

1136
00:52:41,190 --> 00:52:43,650
But really, these might be
people who really just do not

1137
00:52:43,650 --> 00:52:45,360
want to think about
it and are just

1138
00:52:45,360 --> 00:52:46,500
really worried and anxious.

1139
00:52:46,500 --> 00:52:49,800
And they'd rather rule
out that possibility

1140
00:52:49,800 --> 00:52:53,710
of being sick for themselves.

1141
00:52:53,710 --> 00:52:56,230
Now one important
question then is,

1142
00:52:56,230 --> 00:52:58,620
well do individuals
adjust their behaviors?

1143
00:52:58,620 --> 00:52:59,180
Right?

1144
00:52:59,180 --> 00:53:02,770
So far, we talked about,
are people getting tested?

1145
00:53:02,770 --> 00:53:04,330
And the answer is largely no.

1146
00:53:04,330 --> 00:53:08,860
Second, what are people's
beliefs about the disease?

1147
00:53:08,860 --> 00:53:11,435
And people seem to essentially
be overly optimistic.

1148
00:53:11,435 --> 00:53:13,060
Now there's a question,
well, does that

1149
00:53:13,060 --> 00:53:16,180
translate into their behaviors?

1150
00:53:16,180 --> 00:53:20,090
And now this is another
little bit complicated graph.

1151
00:53:20,090 --> 00:53:24,220
But essentially what
the figure shows

1152
00:53:24,220 --> 00:53:27,220
is coefficients relative
to those tested negative

1153
00:53:27,220 --> 00:53:28,600
for Huntington's Disease.

1154
00:53:28,600 --> 00:53:31,550
Let's focus on the black
graphs to start with.

1155
00:53:31,550 --> 00:53:34,930
These are people who are certain
to have the disease, compared

1156
00:53:34,930 --> 00:53:37,850
to people who are
tested negative.

1157
00:53:37,850 --> 00:53:39,550
So what we're comparing
here is people

1158
00:53:39,550 --> 00:53:43,285
who tested positive compared
to people who tested negative.

1159
00:53:43,285 --> 00:53:45,160
And so the coefficients,
if they're positive,

1160
00:53:45,160 --> 00:53:46,535
essentially means
that people are

1161
00:53:46,535 --> 00:53:48,490
more likely to
get divorced, more

1162
00:53:48,490 --> 00:53:51,700
likely to retire, more likely to
change their finances recently

1163
00:53:51,700 --> 00:53:55,450
in their preparation.

1164
00:53:55,450 --> 00:53:58,608
They're also more
likely to be pregnant.

1165
00:53:58,608 --> 00:54:00,400
So they change,
essentially, their behavior

1166
00:54:00,400 --> 00:54:03,298
relative to being negative.

1167
00:54:03,298 --> 00:54:04,840
So this is essentially
just comparing

1168
00:54:04,840 --> 00:54:06,760
positive and negative people.

1169
00:54:06,760 --> 00:54:08,620
I should have said
already, this is a type

1170
00:54:08,620 --> 00:54:13,450
of setting where experiments are
pretty difficult and ethically

1171
00:54:13,450 --> 00:54:17,290
difficult to do, because if
people really derive utility

1172
00:54:17,290 --> 00:54:20,560
from information, providing
people with information

1173
00:54:20,560 --> 00:54:23,180
could really make
them worse off.

1174
00:54:23,180 --> 00:54:26,940
It's quite different from other
sort of experiments involving

1175
00:54:26,940 --> 00:54:30,210
information [AUDIO OUT]
wrong beliefs

1176
00:54:30,210 --> 00:54:33,780
or sort of biased information
about certain outcomes.

1177
00:54:33,780 --> 00:54:35,902
Usually there, you
would say, well let's

1178
00:54:35,902 --> 00:54:37,360
provide them with
good information.

1179
00:54:37,360 --> 00:54:38,977
Maybe they improve
their behavior.

1180
00:54:38,977 --> 00:54:41,310
So there if you provide people
with correct information,

1181
00:54:41,310 --> 00:54:43,590
you could only make
people better off.

1182
00:54:43,590 --> 00:54:47,100
Here, however, since
people derive utility

1183
00:54:47,100 --> 00:54:50,460
from this information, telling
them the truth about stuff

1184
00:54:50,460 --> 00:54:52,050
that they perhaps
didn't know about

1185
00:54:52,050 --> 00:54:54,270
could really make them worse
off and deeply unhappy.

1186
00:54:54,270 --> 00:54:56,980
And so one wants to be
very careful with that.

1187
00:54:56,980 --> 00:55:00,120
And therefore, there are
not a lot of experiments

1188
00:55:00,120 --> 00:55:01,455
in this space, at least for now.

1189
00:55:05,340 --> 00:55:07,140
So the study here
that I'm showing you

1190
00:55:07,140 --> 00:55:09,240
is essentially
observational data.

1191
00:55:09,240 --> 00:55:11,100
And in this case,
comparing people

1192
00:55:11,100 --> 00:55:12,915
who have tested
positive, compared

1193
00:55:12,915 --> 00:55:15,600
to people who tested negative.

1194
00:55:15,600 --> 00:55:17,940
If you look at people who
are just tested recently,

1195
00:55:17,940 --> 00:55:19,710
arguably, these
two types of people

1196
00:55:19,710 --> 00:55:23,070
are not that
different because when

1197
00:55:23,070 --> 00:55:25,800
they made the choice of being
tested, they didn't, of course,

1198
00:55:25,800 --> 00:55:28,990
know whether they were
positive or negative.

1199
00:55:28,990 --> 00:55:30,990
So that comparison
really shows that people

1200
00:55:30,990 --> 00:55:32,470
do adjust their behavior.

1201
00:55:32,470 --> 00:55:34,800
So people who have
been tested positive

1202
00:55:34,800 --> 00:55:38,040
are more likely to change their
lives in pretty dramatic ways.

1203
00:55:38,040 --> 00:55:40,350
For example, people are
more likely to get divorced,

1204
00:55:40,350 --> 00:55:42,270
more likely retire, and so on.

1205
00:55:42,270 --> 00:55:45,610
People are also more
likely to have a pregnancy.

1206
00:55:45,610 --> 00:55:48,270
I think this might
be for women only

1207
00:55:48,270 --> 00:55:52,020
or for couples
with their spouse.

1208
00:55:52,020 --> 00:55:55,810
And that seems like an
interesting result, in a sense.

1209
00:55:55,810 --> 00:55:58,180
That's not what I
would have expected.

1210
00:55:58,180 --> 00:56:03,510
Now that could be in part-- so
the authors in the paper itself

1211
00:56:03,510 --> 00:56:09,210
say that the sample that's
used to look at pregnancies

1212
00:56:09,210 --> 00:56:11,240
is relatively small.

1213
00:56:11,240 --> 00:56:13,650
So maybe in some sense one
needs to be a little cautious

1214
00:56:13,650 --> 00:56:15,820
in interpreting those results.

1215
00:56:15,820 --> 00:56:19,980
It could be that people
try to get pregnant or have

1216
00:56:19,980 --> 00:56:22,290
a child when they
know about the disease

1217
00:56:22,290 --> 00:56:25,080
because they want to
have a child early on.

1218
00:56:25,080 --> 00:56:27,090
There seem to be some
technologies where

1219
00:56:27,090 --> 00:56:30,490
people can, in fact, avoid that
their child had the disease.

1220
00:56:30,490 --> 00:56:33,210
So you could make sure
that doesn't happen.

1221
00:56:33,210 --> 00:56:35,950
And there might be some
couples who might say, well,

1222
00:56:35,950 --> 00:56:40,350
even if it's the case
that one of the parents

1223
00:56:40,350 --> 00:56:43,702
will die early on, if the person
was like 20 years old or the

1224
00:56:43,702 --> 00:56:48,930
like, they might want to have
the child early so they can

1225
00:56:48,930 --> 00:56:51,390
spend sufficiently much
time with the child

1226
00:56:51,390 --> 00:56:54,120
before the onset of the disease.

1227
00:56:54,120 --> 00:56:56,070
But anyway, it seems
to be that people--

1228
00:56:56,070 --> 00:57:00,660
the black lines are
relatively clearly above zero.

1229
00:57:00,660 --> 00:57:03,540
These are coefficients that
compare essentially the black

1230
00:57:03,540 --> 00:57:07,570
versus the group
that's negative,

1231
00:57:07,570 --> 00:57:11,580
which is the positive versus
negative tested people.

1232
00:57:11,580 --> 00:57:14,550
Now when you look at
the uncertain people,

1233
00:57:14,550 --> 00:57:16,410
these are people
who, essentially,

1234
00:57:16,410 --> 00:57:18,090
with some probability,
are positive

1235
00:57:18,090 --> 00:57:20,730
and with some
probability are negative.

1236
00:57:20,730 --> 00:57:22,800
What we would sort of
expect is that those people

1237
00:57:22,800 --> 00:57:25,740
are somewhere in
between the positive

1238
00:57:25,740 --> 00:57:26,860
and the negative people.

1239
00:57:26,860 --> 00:57:29,910
So you would expect that the
gray lines are also positive

1240
00:57:29,910 --> 00:57:33,950
perhaps not as big
as the black lines.

1241
00:57:33,950 --> 00:57:36,360
Instead, you see essentially--
except for the pregnancy

1242
00:57:36,360 --> 00:57:38,790
result, and that doesn't seem
to be significant perhaps

1243
00:57:38,790 --> 00:57:42,300
because the sample is small--

1244
00:57:42,300 --> 00:57:45,500
the gray lines are essentially
pretty close to zero.

1245
00:57:45,500 --> 00:57:49,140
So essentially, people who are
uncertain about the disease

1246
00:57:49,140 --> 00:57:54,547
behave very similarly to
people who are tested negative.

1247
00:57:54,547 --> 00:57:56,505
So essentially, people
who have not been tested

1248
00:57:56,505 --> 00:57:58,380
or who are uncertain
about the disease,

1249
00:57:58,380 --> 00:58:02,640
they behave as if they
were tested negatively

1250
00:58:02,640 --> 00:58:05,970
and likely because they
essentially delude themselves

1251
00:58:05,970 --> 00:58:13,260
in some ways, thinking they are
negative when there's no action

1252
00:58:13,260 --> 00:58:14,550
that they need to take.

1253
00:58:14,550 --> 00:58:17,340
So that really
shows, or the authors

1254
00:58:17,340 --> 00:58:21,450
argue that, essentially
the lack of testing

1255
00:58:21,450 --> 00:58:23,970
really changes
people's behavior.

1256
00:58:23,970 --> 00:58:26,790
Notice that it's very hard for
us to think about welfare--

1257
00:58:26,790 --> 00:58:28,890
are people better or
worse off because of that?

1258
00:58:28,890 --> 00:58:31,140
Because of course,
it's a choice to do so.

1259
00:58:31,140 --> 00:58:32,550
And you might say,
well, I really

1260
00:58:32,550 --> 00:58:34,620
value thinking about
I'm pretty healthy

1261
00:58:34,620 --> 00:58:36,390
and life is going to be good.

1262
00:58:36,390 --> 00:58:38,400
And that's really
valuable to people.

1263
00:58:38,400 --> 00:58:42,780
And they take into account
that changes in their finance

1264
00:58:42,780 --> 00:58:45,852
and so on would be valuable,
but they're not doing this

1265
00:58:45,852 --> 00:58:47,310
because if they
were doing it, they

1266
00:58:47,310 --> 00:58:51,090
would have to acknowledge
to themselves that they are,

1267
00:58:51,090 --> 00:58:52,620
potentially at least, sick.

1268
00:58:58,810 --> 00:58:59,310
OK.

1269
00:58:59,310 --> 00:59:01,685
So how should we think about
these beliefs and behaviors?

1270
00:59:01,685 --> 00:59:03,390
Let me summarize
what we have seen.

1271
00:59:03,390 --> 00:59:06,120
So many people don't get tested,
despite arguably good reasons

1272
00:59:06,120 --> 00:59:07,710
to do so.

1273
00:59:07,710 --> 00:59:10,440
People are often overoptimistic
about the probability

1274
00:59:10,440 --> 00:59:12,990
of not having the disease,
despite often fairly

1275
00:59:12,990 --> 00:59:14,970
clear signs that they have it.

1276
00:59:14,970 --> 00:59:17,490
And that really seems to
be very much consistent

1277
00:59:17,490 --> 00:59:19,322
with anticipatory utility.

1278
00:59:19,322 --> 00:59:21,030
People want to feel
good about themselves

1279
00:59:21,030 --> 00:59:22,290
and about the future.

1280
00:59:22,290 --> 00:59:24,150
And therefore, they're
not getting tested

1281
00:59:24,150 --> 00:59:27,270
and therefore they're
overly optimistic.

1282
00:59:27,270 --> 00:59:30,420
Such over-optimism then
translates into behavior.

1283
00:59:30,420 --> 00:59:32,190
So people react
less to the signs

1284
00:59:32,190 --> 00:59:35,400
of likely having the disease
than they arguably should.

1285
00:59:35,400 --> 00:59:38,100
In particular, people
who are not tested,

1286
00:59:38,100 --> 00:59:40,320
they look a lot
in their behavior

1287
00:59:40,320 --> 00:59:43,260
similar to people who
have been tested negative.

1288
00:59:43,260 --> 00:59:47,670
And that's to say, perhaps if
they were tested positively,

1289
00:59:47,670 --> 00:59:49,920
they would change
their behavior in ways

1290
00:59:49,920 --> 00:59:53,130
that could be useful for
them, at least along the road.

1291
00:59:53,130 --> 00:59:55,950
Now what models can
explain such behaviors?

1292
00:59:55,950 --> 00:59:58,797
It's important to understand
neoclassical models would not

1293
00:59:58,797 --> 01:00:00,880
generate these facts,
because you would say, well,

1294
01:00:00,880 --> 01:00:02,963
you should be tested because
that would be useful.

1295
01:00:02,963 --> 01:00:04,560
And utility is just not--

1296
01:00:04,560 --> 01:00:06,550
there's essentially no
utility from beliefs.

1297
01:00:06,550 --> 01:00:08,275
So why would you not get tested?

1298
01:00:08,275 --> 01:00:09,900
Let's say, well it's
kind of expensive.

1299
01:00:09,900 --> 01:00:13,560
But arguably, the value of
doing so should be quite high.

1300
01:00:13,560 --> 01:00:16,980
And the insurance
would also pay for it

1301
01:00:16,980 --> 01:00:20,000
if you were not
able to afford it.

1302
01:00:20,000 --> 01:00:23,180
Now let me write down or
show you a simple model.

1303
01:00:23,180 --> 01:00:26,330
There will be a problem set,
a question on this model

1304
01:00:26,330 --> 01:00:28,470
for you to understand
it a little better.

1305
01:00:28,470 --> 01:00:29,900
So the model is
extremely simple.

1306
01:00:29,900 --> 01:00:30,950
It has two periods.

1307
01:00:30,950 --> 01:00:34,258
And the relevant outcomes
occur in Period 2.

1308
01:00:34,258 --> 01:00:36,050
In Period 2, the
decision-maker will either

1309
01:00:36,050 --> 01:00:38,822
be negative with probability p.

1310
01:00:38,822 --> 01:00:40,280
So that positive
person essentially

1311
01:00:40,280 --> 01:00:43,220
would be healthy, with probably
p of not having the disease.

1312
01:00:43,220 --> 01:00:47,990
And that person will be
positive with probability 1-p.

1313
01:00:47,990 --> 01:00:52,580
The instantaneous utilities in
Period 2, how they will feel.

1314
01:00:52,580 --> 01:00:55,990
Think about Period 2 as being
everything in the future.

1315
01:00:55,990 --> 01:00:57,560
So Period 1 is the
period when you

1316
01:00:57,560 --> 01:01:00,230
think about potentially getting
tested, which is right now

1317
01:01:00,230 --> 01:01:01,970
or this month or the like.

1318
01:01:01,970 --> 01:01:04,700
And Period 2 now
is, say, next year,

1319
01:01:04,700 --> 01:01:07,250
everything starting
from all of the future.

1320
01:01:07,250 --> 01:01:10,220
Now the instantaneous utility
of this long future period

1321
01:01:10,220 --> 01:01:12,320
are u-minus and u-plus.

1322
01:01:12,320 --> 01:01:16,370
u-minus is if you're negative
so u-minus is the good case.

1323
01:01:16,370 --> 01:01:19,250
And u-plus is if
you're positive.

1324
01:01:19,250 --> 01:01:22,130
You sort of think that
u-minus is larger than u-plus.

1325
01:01:22,130 --> 01:01:26,780
It's better to be negative
than positive in that disease

1326
01:01:26,780 --> 01:01:29,370
or in general.

1327
01:01:29,370 --> 01:01:32,890
In Period 1, we're going to
look at, now, people's choices.

1328
01:01:32,890 --> 01:01:34,880
We can assume no
discounting whatsoever.

1329
01:01:34,880 --> 01:01:36,470
That's just for simplicity.

1330
01:01:36,470 --> 01:01:38,030
We also assume,
for now at least,

1331
01:01:38,030 --> 01:01:41,120
that nothing can be done
about the person's condition.

1332
01:01:41,120 --> 01:01:43,040
So A-- there's no cure.

1333
01:01:43,040 --> 01:01:45,890
B-- there's also no
financial or other adjustment

1334
01:01:45,890 --> 01:01:49,478
that the person might be
able to take to mitigate

1335
01:01:49,478 --> 01:01:50,520
the onset of the disease.

1336
01:01:50,520 --> 01:01:52,270
For now we're going
to just rule that out.

1337
01:01:52,270 --> 01:01:55,220
This is just about, do you
want to find out or not?

1338
01:01:55,220 --> 01:01:57,550
And why or why not?

1339
01:01:57,550 --> 01:02:00,770
Now what would I expect
the utility theory to say?

1340
01:02:00,770 --> 01:02:03,080
Here what is expected utility?

1341
01:02:03,080 --> 01:02:04,010
Well it's very simple.

1342
01:02:04,010 --> 01:02:06,800
It's essentially, there's
no anticipatory utility.

1343
01:02:06,800 --> 01:02:09,710
Expected utility is just what's
going to happen in the future.

1344
01:02:09,710 --> 01:02:12,150
The probability p,
you get u-minus, which

1345
01:02:12,150 --> 01:02:15,050
is the person is negative.

1346
01:02:15,050 --> 01:02:18,530
With probability 1
minus p, the person

1347
01:02:18,530 --> 01:02:22,220
is positive and then
recedes utility u-plus.

1348
01:02:22,220 --> 01:02:24,230
Notice again, there's
no discounting.

1349
01:02:24,230 --> 01:02:25,250
This is in Period 2.

1350
01:02:25,250 --> 01:02:27,730
But then since no
discounting, delta or beta

1351
01:02:27,730 --> 01:02:30,320
are essentially just 1.

1352
01:02:30,320 --> 01:02:33,750
Now let's add anticipatory
utility to this model.

1353
01:02:33,750 --> 01:02:38,900
Notice that this type
of utility can only

1354
01:02:38,900 --> 01:02:40,910
depend on the
person's beliefs about

1355
01:02:40,910 --> 01:02:44,180
whether she will have the
disease or not, not on what

1356
01:02:44,180 --> 01:02:45,420
actually happens.

1357
01:02:45,420 --> 01:02:45,920
Right?

1358
01:02:45,920 --> 01:02:48,110
So the anticipatory
utility depends

1359
01:02:48,110 --> 01:02:51,830
on the probability of
having the disease,

1360
01:02:51,830 --> 01:02:54,810
and not on the actual
consequences of the disease.

1361
01:02:54,810 --> 01:02:58,520
And since the person in Period
1 has this anticipatory utility,

1362
01:02:58,520 --> 01:03:02,240
doesn't know for sure whether
she is going to have it or not,

1363
01:03:02,240 --> 01:03:05,210
the anticipatory utility will
only depend on the beliefs,

1364
01:03:05,210 --> 01:03:08,750
on the probability p for
perceived probability

1365
01:03:08,750 --> 01:03:11,390
p of having the disease.

1366
01:03:11,390 --> 01:03:15,000
Now we're going to make
two extreme assumptions

1367
01:03:15,000 --> 01:03:17,810
about the formation of beliefs.

1368
01:03:17,810 --> 01:03:19,830
Number one is
beliefs are correct,

1369
01:03:19,830 --> 01:03:22,080
in the sense that the
decision-maker will always

1370
01:03:22,080 --> 01:03:25,140
optimally update their beliefs.

1371
01:03:25,140 --> 01:03:28,680
And once you've given the
decision-maker a test,

1372
01:03:28,680 --> 01:03:32,550
the person cannot just make up
their beliefs in certain ways.

1373
01:03:32,550 --> 01:03:35,070
If the test is positive, the
person knows they're positive.

1374
01:03:35,070 --> 01:03:38,200
It's negative, a person
knows that they're negative.

1375
01:03:38,200 --> 01:03:41,070
So p is either 1 or 0
once they have the test.

1376
01:03:41,070 --> 01:03:46,200
Or p is correct in the sense
that the person knows it's p

1377
01:03:46,200 --> 01:03:51,040
and there's no wrong
information or beliefs about it.

1378
01:03:51,040 --> 01:03:53,500
Second, the
decision-maker can choose

1379
01:03:53,500 --> 01:03:55,450
to manipulate her beliefs.

1380
01:03:55,450 --> 01:03:56,950
We're going to start
with one, which

1381
01:03:56,950 --> 01:03:59,830
is essentially the assumption
that beliefs are correct.

1382
01:03:59,830 --> 01:04:04,060
Let the anticipatory utility
in Period 1 be f of p.

1383
01:04:04,060 --> 01:04:07,120
And recall that p is the
probability of being negative.

1384
01:04:07,120 --> 01:04:09,760
Now let's assume that, which
is obvious in some ways

1385
01:04:09,760 --> 01:04:13,030
and uncontroversial that
u-minus is larger than u-plus.

1386
01:04:13,030 --> 01:04:16,570
So essentially, again, remember
u-minus is the probability

1387
01:04:16,570 --> 01:04:17,400
of being negative.

1388
01:04:17,400 --> 01:04:19,810
So utility is higher
in the second period

1389
01:04:19,810 --> 01:04:22,060
if you're negative than
when you're positive.

1390
01:04:22,060 --> 01:04:25,210
And then f of p, f
is increasing in p.

1391
01:04:25,210 --> 01:04:27,940
That's actually not so obvious
in the sense it's not obvious

1392
01:04:27,940 --> 01:04:31,630
that going from a
certain percentage

1393
01:04:31,630 --> 01:04:35,590
to a higher one, the
anticipatory utility

1394
01:04:35,590 --> 01:04:37,180
always increases.

1395
01:04:37,180 --> 01:04:38,890
It's a reasonable
assumption, but one

1396
01:04:38,890 --> 01:04:41,055
might be arguing about it.

1397
01:04:41,055 --> 01:04:43,180
But for now, we're going
to just assume that f of p

1398
01:04:43,180 --> 01:04:45,040
is increasing in p.

1399
01:04:45,040 --> 01:04:48,673
Now does the person
want to know her status?

1400
01:04:48,673 --> 01:04:49,840
Well let's think about this.

1401
01:04:49,840 --> 01:04:54,410
So if she doesn't
find out her status,

1402
01:04:54,410 --> 01:04:59,920
her utility is f of p,
which is her probability.

1403
01:04:59,920 --> 01:05:02,785
Or without finding
anything else is p.

1404
01:05:02,785 --> 01:05:05,350
So f of p is just her
anticipatory utility,

1405
01:05:05,350 --> 01:05:06,860
plus the term that
we had before,

1406
01:05:06,860 --> 01:05:09,865
which is just the expected
utility in the future in Period

1407
01:05:09,865 --> 01:05:16,360
2, which is p times u-minus,
plus 1 minus p, times u-plus.

1408
01:05:16,360 --> 01:05:18,220
Now if she finds
out her status, she

1409
01:05:18,220 --> 01:05:22,450
might find out that she's
either negative or positive.

1410
01:05:22,450 --> 01:05:25,990
If she's negative, that's
with probability p,

1411
01:05:25,990 --> 01:05:27,910
her utility is the
anticipatory part.

1412
01:05:27,910 --> 01:05:29,920
If she's negative,
she just gets f of 1.

1413
01:05:29,920 --> 01:05:31,880
She knows for sure
that she's negative.

1414
01:05:31,880 --> 01:05:36,100
So there she is f of 1, plus
u-minus in the second period.

1415
01:05:36,100 --> 01:05:38,410
All that, again, is
with probability p.

1416
01:05:38,410 --> 01:05:42,700
If she's positive,
her utility is f of 0.

1417
01:05:42,700 --> 01:05:46,100
So her probability of
being negative is 0.

1418
01:05:46,100 --> 01:05:49,600
And then in the second
period, you have u-plus.

1419
01:05:49,600 --> 01:05:52,420
Again, that is
probability 1 minus p.

1420
01:05:52,420 --> 01:05:56,500
So now her expected utility,
putting these things together,

1421
01:05:56,500 --> 01:06:01,150
is the part here in the back,
which is p times u-minus,

1422
01:06:01,150 --> 01:06:04,360
plus 1 minus p, times u-plus.

1423
01:06:04,360 --> 01:06:06,370
That's what we
already had above.

1424
01:06:06,370 --> 01:06:09,850
That's just the expected
utility of Period 2.

1425
01:06:09,850 --> 01:06:16,480
And p times a negative
test, which is f of 1,

1426
01:06:16,480 --> 01:06:21,850
plus 1 minus p, a positive
test, which is f of 0.

1427
01:06:21,850 --> 01:06:22,480
OK.

1428
01:06:22,480 --> 01:06:25,153
And so now, if you
want to figure out,

1429
01:06:25,153 --> 01:06:26,320
does she want to get tested?

1430
01:06:26,320 --> 01:06:30,400
We just have to
compare 1 versus 2--

1431
01:06:30,400 --> 01:06:34,060
or 2 minus 1 if you want, if
that's the value of getting

1432
01:06:34,060 --> 01:06:35,050
tested.

1433
01:06:35,050 --> 01:06:37,270
Notice that the
expected utility part,

1434
01:06:37,270 --> 01:06:38,920
what's going to
happen in the future,

1435
01:06:38,920 --> 01:06:40,510
will always be the same.

1436
01:06:40,510 --> 01:06:44,800
We have p u-minus,
plus 1 minus p, u-plus.

1437
01:06:44,800 --> 01:06:46,370
We have that here as well.

1438
01:06:46,370 --> 01:06:50,230
The reason for that is because
we assumed previously that we

1439
01:06:50,230 --> 01:06:52,043
cannot change the outcome.

1440
01:06:52,043 --> 01:06:52,850
Right?

1441
01:06:52,850 --> 01:06:57,280
So that's going to cancel
out if we subtract 2 minus 1.

1442
01:06:57,280 --> 01:07:01,210
So what we're going to be
left with is essentially

1443
01:07:01,210 --> 01:07:03,910
an expression that
depends on f of p.

1444
01:07:03,910 --> 01:07:10,740
p times f of 1, plus
1 minus p, f of 0.

1445
01:07:10,740 --> 01:07:12,990
When does she reject
or seek information?

1446
01:07:12,990 --> 01:07:18,060
Well she's information-averse
if p times f of 1,

1447
01:07:18,060 --> 01:07:22,740
plus 1 minus p, times f of
0 is smaller than f of p.

1448
01:07:22,740 --> 01:07:24,750
That's exactly-- if you
thought that's the case,

1449
01:07:24,750 --> 01:07:26,640
it's exactly like the
concavity condition.

1450
01:07:26,640 --> 01:07:30,850
If f is concave, that's in fact
the definition of concavity.

1451
01:07:30,850 --> 01:07:33,810
So if f is steeper
for lower values,

1452
01:07:33,810 --> 01:07:38,310
then the person will
be information-averse.

1453
01:07:38,310 --> 01:07:42,150
So if the person really dislikes
any suspicion of bad news,

1454
01:07:42,150 --> 01:07:44,610
for example, due to
anxiety, there's not

1455
01:07:44,610 --> 01:07:49,290
much value-added
certainty, then the person

1456
01:07:49,290 --> 01:07:53,570
will not get tested and
not seek information.

1457
01:07:53,570 --> 01:07:58,490
In contrast, that
function is convex,

1458
01:07:58,490 --> 01:08:01,760
that is to say, if it's
steeper for higher value,

1459
01:08:01,760 --> 01:08:04,400
than the person really
likes certainty.

1460
01:08:04,400 --> 01:08:07,910
So some suspicion of bad
news is not so painful.

1461
01:08:07,910 --> 01:08:09,410
That is to say, so
essentially, when

1462
01:08:09,410 --> 01:08:13,400
you think about p starting with
something like 50%, what you

1463
01:08:13,400 --> 01:08:17,960
want to compare is going from
50% to 100%, versus some 50%

1464
01:08:17,960 --> 01:08:19,010
to 0.

1465
01:08:19,010 --> 01:08:22,939
And going from 50% to
100% is more valuable.

1466
01:08:22,939 --> 01:08:27,920
It improves your anticipatory
utility more than going

1467
01:08:27,920 --> 01:08:35,260
from 50% to 0% is sort of
damaging of p of p-negative.

1468
01:08:35,260 --> 01:08:38,240
It's a little
confusing notation.

1469
01:08:38,240 --> 01:08:41,060
Then essentially the person
will seek information.

1470
01:08:41,060 --> 01:08:44,510
And it's the opposite if
the person really dislikes

1471
01:08:44,510 --> 01:08:49,250
any suspicion of bad news.

1472
01:08:49,250 --> 01:08:52,910
And there's not much
added value of certainty.

1473
01:08:52,910 --> 01:08:56,930
Now that is essentially
just a question of,

1474
01:08:56,930 --> 01:08:58,580
what does this f
function look like?

1475
01:08:58,580 --> 01:09:00,372
And we're going to try
to figure out or try

1476
01:09:00,372 --> 01:09:02,020
to estimate that function.

1477
01:09:02,020 --> 01:09:07,130
Notice that it's a very simple
example here, where essentially

1478
01:09:07,130 --> 01:09:08,960
the person has to always--

1479
01:09:08,960 --> 01:09:11,660
there's no self-delusion
of self-deception.

1480
01:09:11,660 --> 01:09:17,029
The person always had
to adhere to the truth.

1481
01:09:17,029 --> 01:09:19,910
Now consider instead
the possibility

1482
01:09:19,910 --> 01:09:21,890
that the person can
manipulate their beliefs

1483
01:09:21,890 --> 01:09:23,810
to make yourself feel better.

1484
01:09:23,810 --> 01:09:26,000
Now one question you
might ask yourself as well

1485
01:09:26,000 --> 01:09:27,560
in the above
framework, would you

1486
01:09:27,560 --> 01:09:29,090
want to hold correct beliefs?

1487
01:09:29,090 --> 01:09:31,640
Is there any good reason
to hold correct beliefs?

1488
01:09:31,640 --> 01:09:33,439
And the answer is clearly no.

1489
01:09:33,439 --> 01:09:37,899
Well there's no instrumental
reason of beliefs.

1490
01:09:37,899 --> 01:09:38,970
There's no cure.

1491
01:09:38,970 --> 01:09:40,700
You can't really
make anything better.

1492
01:09:40,700 --> 01:09:43,880
You can't really adjust
your behavior by assumption

1493
01:09:43,880 --> 01:09:44,720
currently.

1494
01:09:44,720 --> 01:09:47,660
So why you would you
ever think that you

1495
01:09:47,660 --> 01:09:50,990
have to do this if you can
make yourself feel better

1496
01:09:50,990 --> 01:09:53,340
by increasing your p?

1497
01:09:53,340 --> 01:09:57,830
So if she could believe that
she's HD-negative, for sure she

1498
01:09:57,830 --> 01:10:01,730
would get higher utility
for whatever happens later,

1499
01:10:01,730 --> 01:10:06,620
which is f of 1 is larger
than f of 0, or f of 1

1500
01:10:06,620 --> 01:10:08,640
is larger than any f of p.

1501
01:10:08,640 --> 01:10:09,140
Right?

1502
01:10:09,140 --> 01:10:11,375
Essentially f of p is maximized.

1503
01:10:11,375 --> 01:10:13,190
We assume that it's increasing.

1504
01:10:13,190 --> 01:10:15,560
It's maximized that p equals 1.

1505
01:10:15,560 --> 01:10:18,805
So really in the model
that I showed you so far,

1506
01:10:18,805 --> 01:10:20,180
if you could choose
your beliefs,

1507
01:10:20,180 --> 01:10:21,980
there's really no
reason whatsoever

1508
01:10:21,980 --> 01:10:25,340
of not choosing f of 1.

1509
01:10:25,340 --> 01:10:27,530
When there's a question,
well why might you

1510
01:10:27,530 --> 01:10:29,690
not want to choose f 1 anyway?

1511
01:10:29,690 --> 01:10:31,190
And of course, the
answer is, well

1512
01:10:31,190 --> 01:10:33,680
that's because there might
be instrumental reason.

1513
01:10:33,680 --> 01:10:35,240
There might be
actually some action

1514
01:10:35,240 --> 01:10:38,670
that you might be able to
take to adjust your beliefs.

1515
01:10:38,670 --> 01:10:40,220
So in particular,
incorrect beliefs

1516
01:10:40,220 --> 01:10:41,718
can lead to mistaken decisions.

1517
01:10:41,718 --> 01:10:43,385
You can essentially
make worse decisions

1518
01:10:43,385 --> 01:10:45,450
if you have incorrect beliefs.

1519
01:10:45,450 --> 01:10:48,240
So then there's a trade-off.

1520
01:10:48,240 --> 01:10:48,740
Right?

1521
01:10:48,740 --> 01:10:51,330
There's a trade-off
between, on the one hand,

1522
01:10:51,330 --> 01:10:53,990
if you have incorrect beliefs,
if you're overly optimistic,

1523
01:10:53,990 --> 01:10:55,310
you feel good about it.

1524
01:10:55,310 --> 01:10:57,830
And you're happier than
you would be otherwise

1525
01:10:57,830 --> 01:11:00,610
because you get to enjoy
anticipatory utility.

1526
01:11:00,610 --> 01:11:02,360
But of course, that
might come at the cost

1527
01:11:02,360 --> 01:11:05,040
of making wrong decisions.

1528
01:11:05,040 --> 01:11:09,860
So in that trade-off in
general, decision-making

1529
01:11:09,860 --> 01:11:13,940
with anticipatory utility,
it's like overoptimism leads

1530
01:11:13,940 --> 01:11:16,730
to higher utility than realism.

1531
01:11:16,730 --> 01:11:19,640
That is to say that if you're
fully optimizing to start with,

1532
01:11:19,640 --> 01:11:23,570
some overoptimism would make you
better off because essentially

1533
01:11:23,570 --> 01:11:26,228
you get the value
of overoptimism

1534
01:11:26,228 --> 01:11:28,520
and then you're not going to
distort your behavior very

1535
01:11:28,520 --> 01:11:30,740
much if you were
optimizing to start with.

1536
01:11:30,740 --> 01:11:38,300
So generally you can show that
slight optimism, in many cases,

1537
01:11:38,300 --> 01:11:42,475
in fact, an optimal thing to do,
even if it comes at some cost.

1538
01:11:42,475 --> 01:11:43,850
And of course,
the intuition here

1539
01:11:43,850 --> 01:11:46,460
is that the person wants to
believe that she's healthy,

1540
01:11:46,460 --> 01:11:47,760
and it makes her feel better.

1541
01:11:47,760 --> 01:11:51,890
So she convinced herself that
that's, in fact, the case.

1542
01:11:51,890 --> 01:11:55,400
Now optimal expectations,
essentially, as I said,

1543
01:11:55,400 --> 01:11:58,670
trade-off-- anticipatory utility
versus the value of knowledge

1544
01:11:58,670 --> 01:12:00,515
for making correct choices.

1545
01:12:03,190 --> 01:12:06,110
And then, as I said,
overly positive beliefs

1546
01:12:06,110 --> 01:12:08,150
are an economic
important implication

1547
01:12:08,150 --> 01:12:09,770
of utility from beliefs.

1548
01:12:09,770 --> 01:12:12,740
So once you assume or
think about that there

1549
01:12:12,740 --> 01:12:17,330
might be utility from
beliefs, then one corollary is

1550
01:12:17,330 --> 01:12:20,570
that people tend to have
overly positive beliefs,

1551
01:12:20,570 --> 01:12:24,230
because you explained that
with utility from beliefs--

1552
01:12:24,230 --> 01:12:26,300
because really people
have incentives

1553
01:12:26,300 --> 01:12:29,690
to be overly
optimistic even if that

1554
01:12:29,690 --> 01:12:35,000
comes at the cost of potentially
making worse choices.

1555
01:12:35,000 --> 01:12:37,910
Next I'm going to show
you some other evidence

1556
01:12:37,910 --> 01:12:39,402
of overly optimistic beliefs.

1557
01:12:39,402 --> 01:12:40,860
And then in
particular, we're going

1558
01:12:40,860 --> 01:12:46,370
to talk about heuristics and
biases, which is again the idea

1559
01:12:46,370 --> 01:12:49,430
that people might be
not good patients,

1560
01:12:49,430 --> 01:12:53,510
in the sense that they might
not be good at understanding

1561
01:12:53,510 --> 01:12:57,360
probabilities and how to update
probabilities accordingly.

1562
01:12:57,360 --> 01:13:01,730
Remember, recitation on
Thursday and on Friday

1563
01:13:01,730 --> 01:13:04,900
is going to talk about
Bayesian learning.

1564
01:13:04,900 --> 01:13:07,190
So if you want a
refresher on that,

1565
01:13:07,190 --> 01:13:09,650
that'll be quite helpful
because on Monday we're

1566
01:13:09,650 --> 01:13:12,790
going to talk about deviations
from Bayesian learning.

1567
01:13:12,790 --> 01:13:14,820
Thank you very much.