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Richard Thaler: “The Behavioralizing of Economics” | Talks at Google

Richard Thaler: “The Behavioralizing of Economics” | Talks at Google

Published on Dec 9, 2015
Economist Richard Thaler visited Google’s office in Cambridge, MA to discuss the topic “The Behaviorializing of Economics: Why Did It Take So Long?”.

The talk is an introduction to his book “Misbehaving“. He points out that economic models are based on ideal entities he calls “econs”. But maybe economic choices are made by entities we might call “humans”.

Richard Thaler is an American economist and the Ralph and Dorothy Keller Distinguished Service Professor of Behavioral Science and Economics at the University of Chicago Booth School of Business. He is the coauthor of the best-selling book “Nudge” with Cass R. Sunstein, and the author of “Quasi Rational Economics“, “The Winner’s Curse“, and “Misbehaving: The Making of Behavorial Economics“.

Misbehaving Richard Thaler

:09
Welcome to Talks at Google in Cambridge, Massachusetts.
0:13
Today it’s my great pleasure to introduce Richard Thaler.
0:17
Don’t get too comfortable while you’re enjoying your lunch,
0:20
because Dr. Thaler is here today to change the way you
0:24
think about economics.
0:27
In his newest book, “Misbehaving: The Making
0:30
of Behavioral Economics,” he shows we
0:33
wacky humans don’t, in fact, make the kind
0:36
of rational decisions that traditional economics has
0:39
assumed in creating its models.
0:43
At first, these deviations from the assumed norm
0:45
were dismissed, but now our miscalculations
0:49
and their effects are the subject of serious study.
0:52
The book couples recent discoveries
0:54
in psychology with a practical understanding of incentives
0:58
and market behavior to tell us how
1:00
to make smarter decisions in an increasingly complex world.
1:05
Richard Thaler is an American economist and the Ralph
1:08
and Dorothea Keller Distinguished Service Professor
1:11
of Behavioral Science and Economics
1:14
at the University of Chicago Booth School of Business.
1:17
He is the co-author of the bestselling book “Nudge”
1:21
with Cass R. Sunstein and the author of “Quasi-Rational
1:25
Economics and the Winner’s Curse.”
1:27
Please join me in welcoming Richard Thaler.
1:29
[APPLAUSE]
1:32
1:35
RICHARD THALER: OK.
1:36
Thank you very much for having me.
1:38
The title I’ve chosen for the talk today
1:41
is “The Behavioralizing of Economics:
1:44
Why Did it Take So Long?”
1:47
And this will give you a little taste
1:50
of what the book is about.
1:52
So it seems reasonable to start with a definition of what
1:58
is behavioral economics.
2:00
And as one of my predecessors, Herb Simon, Nobel Prize winner,
2:09
wrote this– the phrase “behavioral economics” appears
2:13
to be a pleonasm.
2:16
A free book to anyone who knows what that word means.
2:21
It’s a redundant phrase.
2:24
And so Simon is right, that it does
2:27
seem to be a redundant phrase.
2:29
Why do we need the adjective “behavioral?”
2:32
What other kind of economics could there be?
2:35
And then he answers his own question.
2:38
The answer lies in the specific assumptions
2:42
about human behavior that are made
2:44
in neoclassical economic theory.
2:46
So that theory is based on the assumption
2:50
that agents in the economy optimize.
2:53
They choose the best thing all the time.
2:56
Is that accurate?
2:58
So the idea is that economists think that the world is
3:04
populated by people like Spock.
3:06
[AUDIO PLAYBACK]
3:07
-My choice will be a logical one.
3:09
[END PLAYBACK]
3:09
Cold-hearted, rationalizing optimizers.
3:13
And I entertain the possibility that there
3:16
are some Homer Simpsons around.
3:18
[AUDIO PLAYBACK]
3:19
-Woo-hoo!
3:19
[END PLAYBACK]
3:20
So how do they differ?
3:21
3:25
The people that populate economic models I call econs.
3:30
And they’re perfect calculators, rational expectations.
3:37
They have no self-control problems.
3:39
They never are on a diet, because they
3:42
eat just the right amount.
3:43
They never have hangovers, because they
3:46
drink the right amount.
3:48
And they’re complete jerks.
3:51
Humans are dumber, weaker willed, and nicer.
3:59
Here’s an illustration of the fact that they’re nicer.
4:05
This is a picture I took in Ithaca,
4:08
where I lived for many years teaching at Cornell.
4:12
A farmer puts this stand up.
4:16
This time of year, he was selling rhubarb.
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And it’s an honor box.
4:22
You put in your money, and you take your rhubarb.
4:26
Notice there’s a box here, and it’s got a lock on it.
4:33
And I think the farmer has just the right model
4:37
of human nature, which is there are enough honest people
4:42
that it’s worthwhile for him to put the corn or rhubarb out
4:47
there and enough people will put money in the box for him
4:52
to be willing to do that.
4:53
But if he left all the money out on a plate,
4:56
somebody would steal it.
4:58
When I first started teaching, I had the following problem.
5:03
I gave an exam, and the students got mad at me.
5:10
And the reason they got mad at me was the average grade
5:13
on the exam was 72.
5:16
These were Cornell MBA students, so they
5:19
were top students from top universities,
5:22
not used to getting grades like 72.
5:26
And I told them, look, what difference does it make?
5:30
We grade on a curve here.
5:31
5:34
The curve was some inflated thing.
5:37
And so it really doesn’t matter what that number is.
5:40
But they were still mad at me, so I had to figure out
5:43
a way of solving that problem.
5:45
So the next exam I gave, I made out of 137 points.
5:52
And the average grade on that was– it was a harder exam.
5:56
The average was 70%.
5:59
But that computed to 96, and they were delighted.
6:04
And in fact, some people got scores over 100,
6:08
and they were in ecstasy.
6:11
So this is an illustration of what I call
6:20
supposedly irrelevant factor.
6:23
So economists disagree about all kinds of things,
6:28
like whether we should fix the economy
6:31
by having the government spend more or less.
6:35
It would seem to be pretty basic that we could get that one
6:38
right, but you can find economists
6:40
arguing on both sides of that.
6:42
But one thing economists all believe in
6:47
is that there’s some stuff that just doesn’t matter.
6:50
So for example, the number of points available on the exam
6:54
should not matter.
6:55
6:58
And there are lots of other things.
7:04
Some costs shouldn’t matter.
7:08
How much you paid for some dessert
7:11
shouldn’t influence how much of it
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you will eat if you’re already full and it’s very fattening.
7:18
But if you’re human, then the more you paid for that dessert,
7:22
the worse you feel about not eating it.
7:25
So I started collecting examples of supposedly irrelevant
7:31
factors, but economists were not impressed with these.
7:37
And they had a long list of excuses
7:40
why these things don’t matter.
7:44
And let’s talk about some of those.
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So an early one came from the famous Chicago school
7:53
economist Milton Friedman.
7:55
And it has just a two-word– as if.
8:00
And in fact, economists can dismiss
8:03
an argument with the wave of a hand and the phrase “as if.”
8:07
And so what does as if means?
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It means we don’t care whether people
8:12
can’t compute these things that you assume they can do.
8:17
All we care about is whether they behave as if they could.
8:23
And so the fact that people are incapable of figuring out
8:29
how much they need to save for retirement
8:31
doesn’t matter as long as they behave as if they can.
8:35
And this was taken to– this was a winning argument for 30 years
8:44
until two psychologists named Daniel Kahneman and Amos
8:48
Tversky came along.
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And they had an insight, which was
8:55
that there are predictable circumstances where people
8:59
make predictable mistakes.
9:02
So for example, they coined the term “the availability
9:05
heuristic,” which is when people judge frequency
9:09
by ease of recall.
9:12
And that’s typically a good idea.
9:17
Things are usually more frequent if you can think
9:21
of lots of examples of them.
9:24
John is a common name, and you know lots of people named John,
9:29
but it sometimes can lead you astray.
9:32
So for example, people think there
9:34
are more homicides than suicides when, in fact, there are
9:38
about twice as many suicides.
9:41
But homicides get more press, and so they’re more available.
9:45
And so we make a mistake.
9:47
And this example illustrates a simple refutation
9:52
of the as if argument, or the more general argument
9:56
that we don’t care whether people
9:58
make mistakes, because if they cancel out,
10:00
we’ll still be right.
10:02
And the point is, they don’t cancel out,
10:06
because the errors are systematic.
10:08
10:11
Another argument I got for many years
10:13
is, OK, you run some experiment, and people screw up,
10:18
but if we get the stakes high enough,
10:22
then people will get it right.
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And another argument I would hear– often
10:27
from the same person– would be, and in your experiment,
10:33
there’s no real opportunity to learn.
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So I ask you the homicide suicide question once,
10:40
and you get it wrong.
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But if I asked you 100 times and presumably told you the answer,
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then you’d get it right.
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So I’d hear these two arguments.
10:50
And in fact, once at a conference,
10:55
I was hearing both of those from an economist
10:58
called Ken Binmore.
11:00
And it caused me to create what I now
11:02
call the Binmore continuum, which
11:05
is– think about the frequency with which you buy stuff.
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So there’s some stuff like milk that you
11:15
buy almost every time you go to the grocery store.
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Then suits– maybe once a year.
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More often, I guess, if you have to wear them often.
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Houses, maybe once a decade.
11:37
Marriages– most people no more than two or three per lifetime.
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Saving for retirement– most of us only
11:48
get to do that once barring reincarnation.
11:52
So notice as we’re raising the stakes,
11:56
we’re reducing the number of times you get to do it.
12:00
So in fact, there’s simply no reason
12:04
to think that when the stakes go up,
12:07
people are going to get it right more often, because they’ve
12:12
had no opportunity to learn.
12:15
Another argument I would hear is, well, look,
12:18
if the stakes are high enough, people
12:21
will hire some expert to help them.
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But here are three examples of high stakes decisions.
12:30
Do we really think experts are jumping in and helping
12:33
people make great decisions?
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I don’t think so.
12:39
12:41
The whole financial crisis really
12:44
was caused by– it started at the bottom of mortgage brokers
12:50
who were being paid for each mortgage they issued,
12:54
and they didn’t care whether the borrower was capable of paying
13:00
the mortgage back.
13:02
And he wasn’t really giving the borrower very good advice.
13:08
And all the way up the chain, that worked.
13:12
Marriage is a pretty important financial decision.
13:15
Hardly anybody goes to an expert for that.
13:18
And across the board, there’s simply no evidence
13:22
that as we raise the stakes, people do better.
13:27
So let me hide that for a minute and just tell you
13:34
a story about a dinner I had with Amos Tversky,
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one of the two psychologists I mentioned,
13:45
and a guy who was a colleague of mine
13:49
for a while at the University of Rochester,
13:51
and then later moved to the Harvard Business School–
13:54
a guy called Michael Jensen.
13:57
And Jensen, at that time, was a hardcore rational economist
14:02
and hardcore believer in the efficient market
14:05
hypothesis in finance.
14:07
And Amos decided at that dinner to have some fun with him.
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And so Amos started out by asking
14:15
Jensen to describe the decision making of his wife.
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And Mike regaled us with stories of his wife’s pathetic decision
14:27
making.
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And then Amos moved on to members of Congress,
14:33
his dean, his students.
14:38
And basically, anybody Amos could name,
14:42
Jensen thought were economic dolts.
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And then Amos pulls the rug out from under him and says,
14:52
so Mike, here’s the thing I don’t get.
14:55
Everybody you know you think is an idiot,
14:57
but the agents in your models are geniuses.
15:02
What gives?
15:02
15:05
And Mike was nonplussed by this question.
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And he said in a kind of condescending manner, Amos,
15:17
Amos, you just don’t understand.
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Now, Amos Tversky is probably the smartest person
15:23
I’ve ever met.
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There’s hardly anything he didn’t understand or couldn’t
15:27
understand.
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So what is it that Jensen thought he didn’t understand?
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He didn’t understand markets.
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And Jensen launched into what, in the book,
15:43
I call the invisible hand wave.
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[LAUGHTER]
15:50
15:51
Here’s the way the invisible hand wave argument goes.
15:54
15:59
Yeah, in your laboratories, people misbehave,
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but in markets– and then it’s my claim
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that no one has been able to finish that sentence
16:14
with both hands still.
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It’s simply not possible to do it.
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So what exactly is going to happen?
16:28
Suppose that I choose the wrong career.
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16:35
I probably did becoming an economist.
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16:40
And what can you do about it?
16:43
You can’t short my career.
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If I married the wrong spouse, you can’t short our marriage.
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And if I don’t save enough for retirement,
16:56
then you can’t short my rounds of golf when I retire.
17:06
So there’s no way, really, for the market
17:09
to correct the decisions that you make on your own.
17:15
But for many economists, this invisible hand wave argument
17:21
was quite compelling.
17:23
And so I would say we were stalled at some point
17:31
and needed to go out and collect data in markets where people
17:41
are misbehaving and try to show that meaningful stuff is going
17:46
on.
17:47
So the line in bold is really the key point,
17:53
which is it’s much easier to make
17:56
money catering to people’s foibles
18:02
than it is in educating them.
18:06
So the last I looked, $27 billion of extended warranties
18:13
were purchased.
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That’s almost always a mistake for anything small.
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So people are making $27 billion selling those.
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No one is making any money convincing people
18:30
not to buy extended warranties.
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I’ve been saying that for years.
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I haven’t made a nickel off of that.
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So here’s another kind of dismissive argument.
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There was an article written about me in the Chicago Alumni
18:48
Magazine.
18:49
And in good University of Chicago style,
18:53
they go talk to my colleague, Gary Becker,
18:56
whose views on this are approximately mine multiplied
19:02
by minus 1.
19:03
And he said about behavioral economics,
19:09
“the division of labor strongly attenuates, if not eliminates,
19:14
any effects caused by bounded rationality.
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It doesn’t matter if 90% of the people
19:19
can’t do the complex analysis required
19:22
to calculate probabilities.
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The 10% of people who can will end up in the jobs
19:28
where that’s required.”
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So I call this the Becker Conjecture.
19:32
19:35
And basically, he’s saying, don’t worry
19:38
about what Thaler is saying.
19:40
In places where it matters, people
19:44
will be good at this stuff.
19:46
So one of my students and I decided
19:48
to investigate this hypothesis in a high stakes
19:52
situation– namely, the National Football League.
19:56
And I think we’d all agree this is high stakes.
20:01
The owners are billionaires.
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In fact, they have a spare billion,
20:06
which is approximately the cost of buying the cheapest team.
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And they have payrolls, their players, over $130 million
20:15
a year.
20:16
So I think we’d all agree this is high stakes.
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Do things work there in the way they’re supposed to,
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or can we find misbehaving?
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And the market we chose to study is the market for draft picks.
20:34
So as I’m sure most of you know, teams
20:38
pick players in an annual draft in which the worst
20:44
team last year gets the first pick
20:46
and the winner of the Super Bowl gets the last pick,
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and then they repeat that for seven rounds.
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And there’s a market for picks.
20:57
And we estimated the price for those picks.
21:01
And you can see, we estimate it with great precision.
21:05
I’ll show you why in a minute.
21:08
But the first thing to notice about this curve
21:10
is that it’s really steep.
21:13
It says that the value of the first pick
21:16
is worth about five times the value
21:20
of the first pick in the second round.
21:24
So our question is, is that correct?
21:29
Is that market rational?
21:32
If you know some finance, it’s like asking
21:35
when Black and Scholes invented the option pricing
21:39
model, if they had made a math error, what would’ve happened?
21:45
So if you’ve ever played with data,
21:47
you know life doesn’t normally look
21:50
like this with a curve that fits the data almost perfectly.
21:54
We thought maybe we had discovered Newton’s fifth law
21:58
or something like that.
22:00
But instead, what we had discovered
22:03
is something that, in the league,
22:06
they referred to as the chart.
22:08
Somebody at the Dallas Cowboys about 25 years ago– the coach
22:15
there at the time, Jimmy Johnson,
22:17
said, can you tell me what various picks should be worth
22:22
so when people ask us to make trades, we know what to do?
22:26
And he drew that curve by free hand,
22:34
and then translated it into a numerical table.
22:37
And that chart circulated around the league,
22:41
and now all the teams use it.
22:44
So including this year, if you looked at any of the trades,
22:50
they’re almost dead on the numbers in this chart.
22:53
So the first pick is worth $3,000,
22:56
and it says that you could get the seventh and eighth picks
23:03
for the first pick, or you could get– this is the– well,
23:10
we can look up– the 33rd pick is $580,
23:14
so you can get five or six of those for the first pick.
23:17
So is that rational?
23:21
Well, I won’t go through the whole analysis we did.
23:25
But we calculated the value to the team of each player picked
23:35
over a 12-year period.
23:37
And that’s this top curve.
23:40
And you can see they know something,
23:44
meaning that the value of the players
23:47
declines as the draft goes on.
23:52
The first round players are, on average,
23:53
better than second round players, and so forth.
23:57
This line is how much you have to pay those guys.
24:01
Now, what is the value of a player to the team?
24:04
It’s the difference between those.
24:08
It’s what you get minus what you have to pay.
24:12
That’s this line, which, you may notice, is sloping up.
24:18
Let me reproduce that curve here.
24:22
And in the bottom half, I have the first graph
24:26
I showed you, which is the market value of picks.
24:31
The top line is what they’re really worth.
24:34
So remember, you can trade this first pick for five
24:38
of these guys, each of which are worth
24:41
more than the pick you gave up.
24:44
This is major league misbehaving for high stakes,
24:50
for people who should supposedly should be in Becker’s 10%
24:55
of people who get it.
24:59
The biggest stakes market is the financial market.
25:03
And it’s kind of surprisingly the place
25:06
where behavioral economics has had its biggest impact.
25:09
And in 1980, no one would have predicted that.
25:13
In fact, Michael Jensen, the same guy
25:16
who I told the story about with Amos diversity,
25:19
wrote a sentence saying the efficient market hypothesis
25:23
is the best-established fact in social science.
25:28
Now, there are two aspects of the efficient market
25:30
hypothesis.
25:32
One is what I call the no free lunch component, which
25:36
says you can’t beat the market.
25:40
And you can’t predict the future from the past, for example.
25:46
That component of the efficient market hypothesis, I say,
25:51
is approximately true.
25:53
25:55
I say approximately.
25:56
I’m a partner in a money management firm
26:00
that actively tries to beat the market.
26:02
And so far, we can, but not by a lot, and not every year.
26:07
So it’s approximately true.
26:08
It’s hard to beat the market.
26:11
The other part of the hypothesis–
26:12
the more important part– is the assertion that prices– I call
26:17
it the Price is Right Component– that prices
26:20
are equal to intrinsic value.
26:24
So the market value of Google is what it should be.
26:30
Now, for many years, efficient market advocates
26:34
had the comfortable illusion that this part
26:38
of the hypothesis was untestable.
26:42
There’s nothing better in a hypothesis than an inability
26:46
to test it.
26:47
And who can know, after all, what the market value of Google
26:54
is?
26:54
26:57
Nobody can prove that it’s right or wrong.
27:01
So for a long time, that part was not
27:04
really considered testable.
27:06
But we found ways.
27:10
So let me give you one example, a recent example.
27:17
There’s a mutual fund, a closed-end mutual fund,
27:22
which means they sell an initial number of shares,
27:26
and then the shares are traded on the market,
27:29
so you have to go buy shares on the market
27:32
rather than sending money to the fund, which
27:34
means that the price can differ from the value of the assets
27:40
that it holds, which is already embarrassing
27:44
to efficient market advocates.
27:46
So one such fund happens to have the ticker symbol CUBA.
27:53
Now, needless to say, it has exactly zero investments
27:58
in Cuba.
27:59
It’s not legal for Americans to invest in Cuba.
28:04
And frankly, there wouldn’t really
28:06
be anything to invest in even if you could.
28:09
28:12
Now, let me show you a graph.
28:14
The day that President Obama announced
28:18
that he was going to relax relations with Cuba,
28:23
the fund went from a 15% discount to a 70% premium,
28:30
which means you have to pay $170 to get $100 worth of assets,
28:35
whereas you used to be able to get it for $85.
28:40
Now, I can’t tell you what the right price
28:45
of the assets the fund owns is, but I
28:48
can tell you you shouldn’t be paying
28:50
$170 for $100 worth of those assets.
28:55
And whatever those assets are worth,
28:58
they were unaffected by what the President did.
29:01
It’s another supposedly irrelevant fact.
29:03
29:06
We’ve seen lots of examples on a larger
29:09
scale of apparent violations of this component– the crash
29:16
in 1987 when prices fell by 20% on a day
29:20
with no news, the tech bubble in the ’90s, the real estate
29:25
bubble in the 2000s.
29:28
Fischer Black– one of the inventors of the Black Scholes
29:32
formula– in a paper wrote that he
29:36
thinks markets are efficient, meaning prices
29:40
are right within a factor of two.
29:43
I think had he lived long enough to see the tech bubble,
29:47
he would have realized that to three,
29:50
since the NASDAQ went from 5,000 to 1,400.
29:55
And I don’t think we would want to call that efficient.
30:00
If cars were priced right within a factor of three,
30:05
I don’t think we would call that an efficient market.
30:08
So where do I think the field of economics is going?
30:15
I’m calling for something that I cheekily refer
30:18
to as evidence-based economics.
30:22
And again, you might ask what other kind of economics
30:26
there might be.
30:27
And the answer is fiction-based economics.
30:32
Because economic theory is a theory of fictional creatures.
30:38
It might as well be a theory of unicorns.
30:41
Econs don’t exist, so theories based on econs
30:45
are fictional theories.
30:47
And what we need is theories that are based on humans.
30:52
So let me– I’ll conclude with this
30:57
and allow you to just read it.
30:59
It’s the closing sentences of my book.
31:03
And I’ll take whatever questions you have.
31:09
AUDIENCE: So traditional economics
31:12
uses mathematical models a lot.
31:14
Mathematical models naturally need
31:16
to make simplifying assumptions, like all math models do.
31:21
And they can get a lot of neat stuff
31:23
by being able to run around with formulas.
31:26
If you take away that simplification,
31:28
you’ve obviously beaten up on that simplification
31:31
of the rational actor.
31:33
Can you get to a simple enough model to have any math?
31:36
RICHARD THALER: Yeah.
31:37
31:39
So you’ve put your finger on– look, economics–
31:45
and I talk about this at some length
31:47
in the book– economics was behavioral until about 1940.
31:54
Adam Smith was a behavioral economist.
31:58
John Maynard Keynes was a great behavioral economist.
32:03
It has nothing to do with whether we
32:05
should have deficit spending.
32:07
Just read his chapter on financial markets.
32:11
It’s a brilliant bit of behavioral economics.
32:13
Then in the ’40s and ’50s, the mathematical revolution
32:18
started.
32:20
And you’re right that– the reason why economics
32:26
got more and more rational is because
32:30
of the bounded rationality of economists.
32:33
So the easiest models to write down are of people optimizing.
32:39
Because if you took high school calculus,
32:41
you know how to take a derivative, set it equal to 0,
32:45
and solve.
32:47
So that’s optimizing.
32:50
If people are human and emotional
32:54
and pay attention to supposedly irrelevant factors,
33:00
then that simple model will be false.
33:02
33:05
Now, can you build formal models that capture actual behavior?
33:11
Yes.
33:12
33:15
One example is a theory of decision
33:18
making under uncertainty called prospect theory that
33:23
was developed Khaneman and Tversky in 1979.
33:28
It’s a much better description of how
33:30
people make choices in uncertain situations
33:34
than the previous theory, expected utility theory.
33:38
And there are other– so the new wave of behavioral economics
33:47
includes theorists writing down mathematical models that
33:52
try to capture some aspect of truth.
33:57
What we don’t have and will never have, in my opinion,
34:01
is a new overarching theory.
34:05
If you want one parsimonious theory,
34:09
stick with the one we have.
34:11
It’s just wrong.
34:12
34:15
But we need to have those theories.
34:22
I couldn’t do behavioral finance without efficient market
34:26
hypothesis as a benchmark.
34:27
34:30
And there’s nothing wrong with writing down those models
34:34
unless you start to think they’re true.
34:37
And so one of the reasons we got into trouble,
34:41
into the financial crisis, is that people like Alan Greenspan
34:45
believed the efficient market hypothesis, and didn’t think
34:50
there could be a real estate bubble,
34:52
and didn’t think that banks would give loans to people who
34:58
couldn’t pay the money back.
35:00
And he gave a famous mea culpa speech
35:02
where he admitted this much, but it came a little late.
35:08
Yeah, right here.
35:09
AUDIENCE: My question of the efficient market hypothesis
35:13
was that it was about efficiency of finding
35:17
the true price of things.
35:19
Is that roughly right?
35:20
RICHARD THALER: Well, as I say, it has two components.
35:23
One is the price is right, and the other
35:26
is that prices are unpredictable.
35:28
AUDIENCE: And so on that price is right,
35:32
I’ve had the impression it was inherently wrong,
35:36
because in most big financial transactions
35:40
I’ve been involved with, everybody else is lying
35:42
or concealing information.
35:44
You’re buying the house, and the person
35:47
you’re buying it from carefully doesn’t tell you
35:49
that they think the roof really needs replacing, et cetera.
35:53
RICHARD THALER: Well, so in financial markets,
35:56
the invisible hand wave is like a windmill.
35:58
36:01
Now, a part of that is deserved.
36:05
So if you’re buying a house and you
36:10
buy a house with a leaky roof, there’s
36:13
no trade I can make to exploit that.
36:18
36:21
I could try to sell you my house, but otherwise– now,
36:27
in financial markets, presumably,
36:31
if stuff is going wrong– so when tech prices were soaring
36:37
in the ’90s and companies were selling for 100 times sales
36:43
because there were no profits, so we couldn’t compute price
36:48
earnings ratios– we had to do price sales ratios– you could
36:55
short the NASDAQ.
36:58
But people started worrying that NASDAQ was overvalued in 1996.
37:06
And if you shorted the NASDAQ in ’96,
37:10
you were broke before you were right.
37:13
So financial markets are more efficient than the markets
37:20
for houses and cars, but still not perfectly efficient
37:24
for reasons I go into in some length in the book.
37:28
AUDIENCE: So maybe this is what you’re already saying, but is
37:31
it simply that you can’t predict when people are going
37:33
to stop being wrong, and so it doesn’t matter if they’re
37:36
wrong as long as they stay wrong longer than you can afford
37:38
to disagree with them?
37:40
RICHARD THALER: Yeah.
37:41
I once– yes.
37:43
So I once had a conversation with George Soros,
37:48
the famous hedge fund investor.
37:51
And this was sometime during the late ’90s.
37:53
And I asked him whether he would ever consider just
37:58
shorting the S&P 500, because it certainly
38:04
looked to him and to me like it was too high.
38:10
And he speaks and writes cryptically.
38:17
And his answer was much in character.
38:19
He said that, well, you can bet on prices
38:25
returning to intrinsic value, but you’ll die of boredom.
38:28
38:31
And so that’s the fundamental problem,
38:35
that we can see– I remember having
38:39
a discussion with my brother, who lives in Scottsdale,
38:43
and he had just bought his third property in Scottsdale.
38:47
And I said, diversification, have you heard of that concept?
38:56
You now have three pieces of property
38:58
within four square miles.
39:00
It seems like you have all your eggs in one basket.
39:05
And he said to me– and I’m quoting him precisely– no,
39:12
you don’t understand.
39:15
Real estate prices in Scottsdale never go down.
39:20
Now, if I could have– if there was a broker I could call,
39:26
short Scottsdale, I would have done it.
39:31
But Bob Schiller, my fellow behavioral economist,
39:37
tried to create such markets.
39:41
And there wasn’t enough volume.
39:45
It turned out that that effort was unsuccessful.
39:48
But as a result, there’s no way to short a frothy real estate
39:53
market.
39:53
So many people– certainly Bob Schiller was pointing– well,
40:00
I could have tried to show you a graph.
40:02
But if you plot real estate prices from 1950 to 2000,
40:14
they’re going up on a log scale like it’s a straight line,
40:19
1% to 2% a year.
40:21
And it’s tracking 20 times rental price.
40:27
And then it just shoots off into Never Never Land.
40:33
And in places like Vegas and Scottsdale and South Florida,
40:37
it really just shot off.
40:39
And you had to either think this time, it’s different,
40:44
the world has changed, or jeez, this looks like a bubble.
40:49
But if you think it’s a bubble, it’s
40:51
really hard to take advantage of it,
40:53
and it’s really hard to know when it’s going to break.
40:57
And if you read Michael Lewis’s book “The Big Short,”
41:03
there are guys there who had figured it out,
41:07
and they came very close to going broke
41:11
before they were right.
41:13
And it was a matter of a month or two.
41:18
And that’s the essential problem,
41:21
and that’s why we can have bubbles.
41:24
And many people think that there are very frothy aspects
41:30
of the tech market now.
41:32
41:36
But if you think– well, Uber isn’t listed yet.
41:41
But if it were listed, and you don’t
41:44
think it’s worth $40 or $50 billion, and you sell it short,
41:50
you better be right soon, because you
41:52
start getting margin calls.
41:56
A mic to the gentleman in the back.
41:57
42:01
AUDIENCE: I had a question about your NFL study.
42:03
RICHARD THALER: Finally, football.
42:05
AUDIENCE: Football, yes.
42:06
I can see how compensation is directly observable,
42:09
but how did you estimate the value of the draft pick?
42:14
Because it seems like there lies a lot of assumptions.
42:16
RICHARD THALER: We had performance data.
42:22
For the graph I showed you, we used pretty crude data,
42:28
like games started.
42:29
42:33
And we did that so we could cover all positions.
42:37
But if you replicated– actually,
42:44
Nate Silver was with me at my event last night in New York,
42:49
and he was telling me that he had replicated our study
42:54
for quarterbacks using the most sophisticated
42:58
new analytical measures of quarterback ability.
43:02
And the result was an exact replication,
43:06
which he thought was too boring to publish.
43:09
I almost hit him on the spot, and I’m
43:13
going to have a stern talking to him later.
43:16
43:21
So we can measure– in the places
43:26
where we can measure performance,
43:27
we replicated it for wide receivers, and it works.
43:31
AUDIENCE: Right.
43:32
I’m familiar with the work of Football Outsiders and places
43:34
like that in translating draft picks
43:36
to performance measures, football performance
43:37
in various measures.
43:38
But you still then have to make the translation to financials.
43:41
RICHARD THALER: Yeah.
43:42
So what you do is you look at how much you
43:45
have to pay free agents that are of similar quality,
43:50
and then we assume that market is efficient,
43:54
which could be wrong.
43:56
So the way it works is– take RG3.
44:03
So his first year, he was an all-star quarterback.
44:07
And we look, how much do all-star quarterbacks in years
44:13
six through eight of their contract–
44:15
how much do you have to pay them.
44:17
Then his second year, he’s hurt, so he’s a reserve quarterback.
44:22
Well, that’s, say, worth $4 million.
44:25
So we do that for every player.
44:27
44:32
There are details in the book and in the paper
44:39
on which that chapter is based, which is available online.
44:43
Go to my personal website and you can find them.
44:45
44:48
Any other questions?
44:49
Yeah.
44:50
44:52
AUDIENCE: I have two, so I’ll pick one arbitrarily.
44:56
I have an economist professor friend
44:58
who often likes to say that if you don’t have a model,
45:01
there’s no point to looking at something,
45:03
because you may observe differences,
45:05
but you won’t learn anything unless you
45:06
can compare it to a model that you think models something.
45:11
RICHARD THALER: That’s a very popular thing
45:12
for economists to say.
45:13
AUDIENCE: I’ve read that a lot, so I’ve
45:15
seen that a lot of economists believe that.
45:17
But this as if idea that you gave
45:20
seems to be the opposite of that.
45:22
It seems to say, who cares whether the model represents
45:25
anything at all.
45:26
All that matters is whether you see something.
45:29
RICHARD THALER: Right.
45:30
So I think that models can hide a lot.
45:39
And I think the idea that you can’t learn anything
45:48
without a model is preposterous.
45:51
So there’s no model in our football paper.
45:56
But look at those graphs.
45:58
They tell a pretty powerful story.
46:01
And there is an underlying model,
46:07
which is that prices are equal to intrinsic value.
46:11
And in order to get the paper published,
46:13
we put in some Greek symbols.
46:16
AUDIENCE: But what I wonder is how do you think–
46:18
RICHARD THALER: But they were completely unnecessary.
46:20
AUDIENCE: How do you think economists squared
46:22
these two ideas that seemed to be
46:23
both popular and contradictory?
46:26
RICHARD THALER: You use whichever
46:29
one comes in handy at the time.
46:32
46:35
That may sound unnecessarily cynical,
46:39
but I don’t think I have a better answer.
46:41
Maybe ask your other question.
46:44
AUDIENCE: My other question is this price
46:46
is right idea– or the price is wrong– seems
46:50
to assume there is an actual objective price
46:52
hiding under there somewhere, whether people are getting
46:54
it right or wrong.
46:55
And I wonder what you think of the idea
46:57
that there may not be the, that the right price is just
47:01
defined by whatever people happen
47:03
to think it is right now.
47:04
RICHARD THALER: Well, so that’s the view people had
47:07
when they thought they could hide behind the idea
47:10
that they had a hypothesis you couldn’t test.
47:14
So one of the papers I wrote was on an episode
47:22
during the tech bubble in which the company 3Com happened
47:29
to be the owner of Palm.
47:34
And somebody already knows the punchline of this story.
47:40
So Palm– you will remember if you’re
47:44
old enough– a Palm Pilot was about the size
47:49
of a deck of cards.
47:51
And as far as I could tell, it could keep your contacts
47:56
and also serve as a calculator and maybe a calendar.
48:03
But it was considered pretty sexy.
48:06
And eventually, they had a phone that was the first smartphone.
48:13
Anyway, 3Com owned Palm, but 3Com was not sexy.
48:19
And their stock price was flat in a period
48:22
when any decent technology company was going up 20%
48:26
a month.
48:28
And so they decided to carve out Palm and make it
48:33
a separate company.
48:35
And so they did that, and they had an IPO for Palm.
48:40
But they kept– they only sold 5% of the shares of Palm.
48:45
They kept 95% within the company.
48:50
And then the Palm IPO happened, and Palm– anything
48:56
that looked sexy at that time sold for a ridiculous prize.
48:59
49:01
But here’s an equation.
49:04
I’m going to give you an equation.
49:07
3Com shareholders each got 1.5 shares of Palm.
49:15
Therefore, the price of 3Com– it’s
49:19
an inequality, actually, not an equation.
49:21
The price of 3Com must be greater than 1.5 Palm,
49:29
because companies can’t be worth negative amounts.
49:36
But the day of the Palm IPO– if you computed the stub value
49:45
of 3Com, meaning its price less its interest in Palm,
49:50
it was minus $23 billion.
49:52
49:55
Now, that’s wrong.
50:00
That’s really, really wrong.
50:02
And I talk about in the book– when my co-author and I
50:08
presented this paper at the University or Chicago,
50:11
we ended up getting into a discussion of icebergs.
50:15
And my friend Gene Fama, who’s an efficient market advocate,
50:20
said look, these are trivial examples
50:28
that you’re showing us.
50:33
OK, so this is wrong, but the rest of the market is fine.
50:38
And I was saying, no, this is just the tip of the iceberg.
50:43
And I’ve studied a bunch of these, like the Cuba example.
50:50
And I call them the fruit flies of finance.
50:55
Fruit flies are not a particularly important species
50:58
in the grand scheme of things, but they’ve
51:01
been incredibly useful in genetics.
51:04
And these special cases, like closed end mutual funds,
51:08
and Palm and 3Com, are where we can say
51:12
for sure the price is wrong.
51:15
And so the debate turned.
51:17
Gene was saying that this was the whole iceberg,
51:22
and I was saying it was the tip of the iceberg.
51:24
And it’s a discussion we continue to have to this day.
51:29
51:33
I think our time is up.
51:36
Thank you very much.
51:37
[APPLAUSE]