WEBVTT
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33c3 pre-roll music
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Herald: Err ...
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H: ... a talk would be good, right?
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applause
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Do you want to give a talk?
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Toni: Aah, it’s a little early
but I’ll try.
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Herald: Okay, guys, well, I found someone
who’s willing to give a talk!
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laughter and applause
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That is most excellent.
So, if you ever asked yourself,
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I’ve got this big regime and
I’m rolling out internet censorship,
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what does my economy do?
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There are people in here
asking that question, right?
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There’s always someone at Congress
who’s asking some question.
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Well, you came to the right place,
and as part of her PhD thesis work
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Toni is going answer that question,
hopefully, to a satisfactory point.
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Please give a warm round of applause!
applause
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Toni!
ongoing applause
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Toni: Okay, thanks everyone for being
here, I hope you can all hear me
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correctly. And I’m glad to be here
and to be presenting
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some part of my thesis to day.
Now, this is ongoing work
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so I’m really grateful for any kind of feedback
that you guys would have
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and I’m really only presenting this
as kind of a first try,
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because when I looked at the topic
of internet censorship
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and what that could mean for an economy,
I really didn’t find anything academic
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and I was quite surprised: it seemed
like a very obvious question to me,
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because I was looking mostly
at China at the beginning.
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And I read a lot of newspaper articles
and I talked to a lot of businessmen
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who told me: “Well, doing business
in China is very difficult”
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and I think China is really
holding itself back by having
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this big censorship thing going.
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But no one really looked into
how it is holding itself back
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or if it is even holding itself back.
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So there is really
very, very little research.
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And we don’t even have an agreement among
economists or business studies people
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about what impact the internet has
on the economy. So if you want to ask:
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“So what does internet censorship do
to an economy?” it seems pretty obvious
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to first ask: “What does the internet do to
an economy?” and we don’t even know that.
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That was quite surprising to me and I’m
going to be talking about the reasons
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for that a little bit later on. But in
general, I was thinking of a research
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question to ask which for me is: “Does
internet censorship reduce economic welfare?”
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Now, not all of you are economists,
so some of you might think of welfare
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more as the transfer payments
that a state gives to its poorer people.
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But for economists, economic welfare
is defined as the consumer
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and producer surplus. So basically, the
difference between what something costs
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and what you can sell it for
is the producer surplus.
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The difference between
what you would be willing to pay
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and what you’re actually paying
is your consumer surplus.
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Now let’s assume I have a laptop
and I bought this.
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And I would have been willing to pay
€ 1500 for this laptop because
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I think it’s a very good product,
it’s by Lenovo that makes good laptops.
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But actually I got it for like €800
or €900. That would mean
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my personal consumer surplus
is something like €600 or €700.
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And if we add up everyone’s
individual consumer surplus
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we get the economic welfare surplus.
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So first, I was trying to figure out
what does the internet mean
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for the economy. And I’ve said that there
is really no good agreement on that.
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Now, a very crude measure that I found is
how much does "the Internet economy"
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contribute to GDP?
Now, what is "the internet economy"?
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It wasn’t very clear in the research
that I’ve read. It seems to be sort of
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online retail, and possibly some other
internet-enabled services?
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Possibly but not necessarily
internet advertisement revenue
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is reflected in this. But because it was
BCG, which is a big consulting agency
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that basically published this research
they weren’t very diligent about
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their methods, basically.
So we can see, well it seems that the UK
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has a pretty big part of internet economy
as part of GDP.
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That’s probably mostly because of
online retail which is bigger in the UK
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than in most other countries we look at.
And we see that there is
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a small difference between
developed and developing market averages
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when looking only at the G20 countries.
But this seems like a very
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dissatisfactory answer because first
of all, I don’t know the methods,
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so I can’t really say
whether this is actually good.
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And secondly, GDP is actually
not a good measure
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for what we are trying to measure because
a lot of the stuff that the internet creates,
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a lot of the value the internet creates
isn’t captured by GDP at all.
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One example is free online courses.
Most of the online courses you can take
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on the web are actually free.
And most of them are not ad-enabled.
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So most of them don’t really have
advertisements in the general sense.
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So classical economics basically says:
“Well, they don’t really create any value.”
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But if you’ve ever taken
one of these online courses,
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and maybe you’ve been lucky
and took a good one
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you would actually… I would say that
some of the courses I took,
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they created some value for me.
So one of the ways to look at this
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is actually to think about time as
something that has opportunity cost.
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So if I’m spending my time doing this
online course I’m not spending it
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e.g. earning money. I’m also not
spending it doing something leisurely
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that is fun for me.
And these guys, Brynjolfsson
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– I’m sorry I don’t know
how to pronounce it exactly,
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he sounds Swedish, possibly –
and ohh, in 2012
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they tried to get an idea of
how much consumer surplus
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these online courses actually create.
Which isn’t at all
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reflected in the GDP.
And you see that in some models
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it would be 5% of GDP
for these online courses alone.
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Even if we take their more... most conservative
model which is $4.18 billion
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on average for the years 2008-2011,
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that’s still a pretty significant chunk
of economic welfare
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that’s somehow being created
that is not reflected in GDP
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because GDP is only stuff
that you actually pay money for.
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Another example that we
might think of is Wikipedia.
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Now Wikipedia has a certain cost of
operating: obviously the servers and stuff.
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But because most people contributing
to Wikipedia are actually volunteers
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the cost of operating
does not really reflect
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the true value Wikipedia creates.
And one of the…
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even if you don’t want to say…
even if you don’t agree
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that time has opportunity cost, what
about the money that you don’t spend
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on encyclopedias? How many of you guys
have encyclopedias at home?
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OK, that’s more than I expected!
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How many of you guys have
recent encyclopedias at home?
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That’s a little less, this is kind of more
what I was expecting.
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And now, my family also… we also have
an encyclopedia at home.
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I think it’s from 1985 or something.
And before this encyclopedia
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we would regularly update an encyclopedia,
we would regularly go out and buy
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a new encyclopedia because
knowledge changed, obviously.
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But ever since probably 1990,
we just didn’t bother.
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So, assuming an encyclopedia might,
like a physical book, might cost €100.
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And assuming sort of 2/3
of all households in Germany
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have had an encyclopedia at one point.
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We’re looking at 13 million households
at this point.
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Now you don’t buy an encyclopedia
every year but you might buy it
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every ten years. So in order to simplify
this we can say, every year
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1.3 million households buy
an encyclopedia on average.
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1.3 million times €100,
so we’re at €130 million
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of economic welfare, of something that
people were willing to spend money for
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that they’re not spending money for anymore
because of Wikipedia, because now that
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we have Wikipedia most of the encyclopedias
aren’t actually useful for us anymore
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because the knowledge that we have,
the knowledge that they would have
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would be outdated very, very soon and
Wikipedia tends to be more up to date.
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Well, that was from the consumer’s side.
But what about the business side?
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There’s a lot of research on whether the
internet actually increases productivity
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for businesses or not. Well, I don’t really
want to go into that debate because
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it’s a really long tedious debate that is
kind of focused on “Well, you did this
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method wrong”, or “You did this wrong”,
and “Well, I don’t think your argument
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makes sense”. So it’s very… I don’t like
this kind of debate. I really like to go
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deeper in things. But one of the things
that I found was that a lot of businesses
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do rely on the internet by now. Now
we can see on this graph that most firms,
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overall about 70% of firms actually
use the email to communicate.
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Now email obviously only works
if you have internet, so they need
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some sort of access to internet in order
for their current business model to work.
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Now this was just some short ideas on
sort of what can the internet mean for
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the economy. And now I want to talk about
Internet censorship, just a little bit.
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Now, I’m not a censorship expert. I’m just
someone who read a lot of papers about it,
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and who was very interested in what kind
of effects this has beyond sort of
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the obvious “people don’t have access
to political information”.
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So first a definition. ‘Internet censorship’
is the controller suppression
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of what can be accessed, published
or viewed on the Internet
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enacted by regulators or on their own
initiative. Now, in trying to conceptualize
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internet censorship, for me, personally,
there’s two dimensions that are
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very important. One is how targeted
is this internet censorship?
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Now, you could, in theory, basically
have internet censorship
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that is very, very targeted,
which you see in some cases.
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Or you can have censorship
that isn’t targeted at all, like in Egypt.
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They just decided to close the internet
down, basically, for a day.
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That isn’t very targeted censorship,
obviously. The other thing to look at
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is how widespread is it? So if you are
a business or if you’re a normal consumer
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how probable is it that you would come (?)
something that’s censored?
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Now, obviously, if you’re in China it’s
a lot more probable that you would
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try to access something that’s censored
than if you’re in Germany. Even though
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Germany also does some censorship.
And the way I like to conceptualize it is
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to be kind of on a continuum. So I don’t
look… I don’t say “Well, either
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there’s censorship or there isn’t
censorship”. What I’m trying to say is
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“Censorship has a big spectrum
of things that can happen”.
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These are some types of Internet censorship
that have different sort of implications.
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I don’t want to go through them in detail
because I think we’ve heard some really
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interesting talks on Internet censorship
already. But this is kind of
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interesting or important for the model
that I’m trying to build.
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But before trying to build my model,
first some more motivation.
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I was trying to look at “is there any
evidence that it would have
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an economic impact?”. And there actually
is a study that’s conducted by sort of
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lobbying organizations, so obviously
should be taken with a grain of salt.
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But it is quite interesting, and it shows
that there seems to be a correlation
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between freedom and how good
the economic impact of internet is.
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This is just a simple correlation. You can
see that there’s a really good line
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going through it. They did do some
controlling for GDP per capita, so
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for development level. But it still seems
quite rudimentary, to be honest.
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The data that they use is quite bad
because it is very, very…
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it’s just not finally granular enough, and
a lot of it is kind of… someone rating…
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so “How do you think the economic…”,
“How do you think Internet
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impacts the economy in this country?”
And then this is the data that they use,
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to some degree. So it seemed very…
it didn’t really seem like a good, final answer.
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So I’m trying to set up my own model.
And in my model I have a government
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that chooses the type of censorship. And
for this type of censorship that it chooses
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it pays a cost. Because we all know
censorship can be very expensive.
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And in my model for now the only type of
expenses that I calculate are actual
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manpower and technology expenses. I don’t
calculate reputation expenses at this point.
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There is… there are firms in n industries.
Now this n is kind of not a fixed number
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but instead is a number that can fluctuate
depending on the kind of country
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I’m trying to model. And these industries
distinguish themselves by their
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information intensity, or what I like
to call ‘information intensity’. Basically
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I look at information as a commodity.
And what I’m trying to decide, or
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the way I distinguish different kinds of
industry is how important is information
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as a commodity, as opposed to other kinds
of commodities that are important
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for this industry. So let’s look at
information intensity equals Zero.
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Like if we don’t really… if information
as a commodity really isn’t important,
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especially sort of conveyed information,
transmitted information. We can
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think of traditional agriculture. Now
I know today’s agriculture tends to be
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large-scale, and there’s a lot of
technology involved. But if you look at
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very traditional agriculture that we
still might see happening in some parts
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of Africa there usually is very, very
little information transmission involved.
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And most of the information transmission
that is involved is actually mostly through
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word of mouth. So that would be a case of
information intensity of very close to Zero.
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And then if we look at information intensity
of 1 where basically the internet is
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the most… or information is the most
important commodity. Internet businesses
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themselves would… obviously qualify here,
– sorry – like, let’s look at Facebook
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and other kinds of businesses like this.
And in between we have sort of industrial
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companies in the modern world.
Now if we’re closer to the Zero end
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of the spectrum we might be
at 0.2 .. 0.3, something like this,
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we might be in traditional garment
factories. They do have information needs,
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they get their cuts and stuff from the
Internet by now, or by email.
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But once they have them they basically stay
the same for a couple of weeks or months.
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So there’s a very low information
requirement. On the other side,
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closer to 0.8 or something
like that we have high-tech,
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especially software manufacturing,
so to speak. Information and being able
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to transmit this information is very
important. Now, in between we might look
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at traditional industrial companies
like automobile manufacturing
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that might be somewhere in between.
And before the game, or before…
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or at the first run of the model
‘service level’ and ‘globalization level’
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are randomly distributed. The information
intensity of industries is also kind of
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randomly distributed, but not in a true
random fashion. Because when looking
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in the wild, sort of what kind of
economies exist, most of them…
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the information intensity of one
industry is kind of correlated with
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information intensities of other industries
in this country. Like in Germany
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we’re very known for a certain type
of industry that we have quite a lot of,
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which is manufacturing, very high-technology
manufacturing. So we have more industries
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in this area but we have less traditional
agriculture, for example.
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So having a true random distribution
wouldn’t work. In addition the service level
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and the globalization level are randomly
distributed as kind of external variables.
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Obviously, this is a simplification because
I can’t really start at the beginning like
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I can’t say: “Oh well, I’ll start,
I don’t know, 2000 BC
00:17:58.870 --> 00:18:04.190
with a very blank economy, and then
something happens and something happens
00:18:04.190 --> 00:18:08.320
and something happens”. That’s just not
realistic. So in order to get a better idea
00:18:08.320 --> 00:18:12.830
of what happens with different types of
economies, what I’m doing is I’m running
00:18:12.830 --> 00:18:18.899
this game or this model again and again.
And having these random parameters
00:18:18.899 --> 00:18:24.539
basically changed everytime.
So on average there should be…
00:18:24.539 --> 00:18:29.289
there should be usable results.
00:18:29.289 --> 00:18:35.230
Now what this is actually missing
is the consumer as a labourer.
00:18:35.230 --> 00:18:40.090
So I don’t really have ‘labour’ reflected
in here. A more complete model would have
00:18:40.090 --> 00:18:44.080
that reflected. But it’s not the most
interesting aspect of my model, so
00:18:44.080 --> 00:18:49.940
I’m not presenting this here, basically.
00:18:49.940 --> 00:18:56.080
Now, let’s look at what this would
mean for firms. In my model
00:18:56.080 --> 00:18:59.649
what kind of things would I expect
thinking through it logically which is
00:18:59.649 --> 00:19:04.820
always the first step when trying to model
something. First of all if we have
00:19:04.820 --> 00:19:10.130
an information intensity of something
greater than Zero but smaller than One.
00:19:10.130 --> 00:19:14.410
Because the information intensity being
close to One is kind of a special case
00:19:14.410 --> 00:19:18.520
that I’ll be talking about later on.
Internet censorship increases the cost
00:19:18.520 --> 00:19:22.360
and uncertainty of information.
And of course that is more important
00:19:22.360 --> 00:19:27.850
the more important information is
for this certain industry.
00:19:27.850 --> 00:19:33.850
So for a traditional garment factory
internet censorship might be a lot
00:19:33.850 --> 00:19:41.000
less important than for a semiconductor
factory that has to receive
00:19:41.000 --> 00:19:47.090
new blueprints every day or every month
or something. The second thing is
00:19:47.090 --> 00:19:51.559
the more globalized the economy as a whole
is the more costly internet censorship
00:19:51.559 --> 00:19:58.490
will be. Similar reasoning.
00:19:58.490 --> 00:20:02.990
And another thing for firms is the
less focused the censorship
00:20:02.990 --> 00:20:07.640
the higher the cost. Now this assumes that
the censorship or the goal of censorship
00:20:07.640 --> 00:20:14.370
usually isn’t to turn down firms or to
make sure that firms don’t succeed.
00:20:14.370 --> 00:20:19.820
So if censorship is very focused
firms tend to be affected less
00:20:19.820 --> 00:20:25.149
which makes their associated cost less.
Now of course we can argue, well,
00:20:25.149 --> 00:20:29.399
firms can circumvent censorship, and they
can do that for sure. But it is expensive
00:20:29.399 --> 00:20:35.299
to do that. If you’ve ever tried a VPN
in China e.g., first, buying the VPN
00:20:35.299 --> 00:20:40.919
is expensive. Then, having someone sort of
make sure that the VPN works is expensive,
00:20:40.919 --> 00:20:44.009
every couple of months you need to change
it because the Chinese Government decides,
00:20:44.009 --> 00:20:52.549
well, this VPN shouldn’t work anymore. So
it’s a very expensive and uncertain thing,
00:20:52.549 --> 00:20:57.909
really. For firms in
‘information intensity = 1’
00:20:57.909 --> 00:21:02.940
it obviously also increases the cost
of operating. Some of these firms actually
00:21:02.940 --> 00:21:07.970
carry out some censorship for governments.
We have seen that happening more recently.
00:21:07.970 --> 00:21:12.570
But there might actually be some firms
that have a relative advantage, especially
00:21:12.570 --> 00:21:16.820
domestic firms often have a relative
advantage due to the censorship because
00:21:16.820 --> 00:21:20.950
they know the regulators better, they know
how to deal with it, they might have
00:21:20.950 --> 00:21:25.039
less need to circumvent, actually.
And even if they do need to circumvent
00:21:25.039 --> 00:21:29.539
it’s easier for them because
they speak the language etc.
00:21:29.539 --> 00:21:34.090
This is actually a special case that I’ll
be talking about a little bit later as well.
00:21:34.090 --> 00:21:38.460
For the government – I’ve said
that censorship is costly. But moreover,
00:21:38.460 --> 00:21:43.100
the more targeted and accurate censorship
is the more manpower and technology intensive
00:21:43.100 --> 00:21:50.389
it actually is. This is a finding by
Leberknight et al. in a research paper.
00:21:50.389 --> 00:21:54.480
I think they’re electrical engineers, and
they calculated through different types
00:21:54.480 --> 00:22:00.350
of censorships and how expensive it would
be to scale them up. So that is actually
00:22:00.350 --> 00:22:03.479
a really interesting finding because
it shows that for governments
00:22:03.479 --> 00:22:10.460
having sort of less targeted censorship
is less costly. But this is the kind of
00:22:10.460 --> 00:22:17.039
censorship that is actually most affecting
in a negative way to firms,
00:22:17.039 --> 00:22:20.990
in an economy. So that’s kind of not
a result that we would really want
00:22:20.990 --> 00:22:24.919
because the incentives don’t line up in
that way. And economists love to talk
00:22:24.919 --> 00:22:29.169
about incentives, obviously. Now for
consumers, they would obviously get
00:22:29.169 --> 00:22:33.090
less benefits through the internet, the
benefits that I’ve talked about before.
00:22:33.090 --> 00:22:38.430
And also businesses often pass on the cost
to consumers.
00:22:38.430 --> 00:22:43.350
Now however, some countries
still benefit from internet censorship.
00:22:43.350 --> 00:22:45.970
I’ve talked mostly
about why it’s costly to do it,
00:22:45.970 --> 00:22:48.700
and I think it is costly in most cases.
00:22:48.700 --> 00:22:53.210
But developing countries that start out at
low service and low globalization levels
00:22:53.210 --> 00:22:58.950
usually have… in these kind of situations
internet censorship has less of an impact,
00:22:58.950 --> 00:23:04.370
less of a negative impact.
And censorship can actually act
00:23:04.370 --> 00:23:08.880
as protectionism. In information intensive
industries governments can use this kind
00:23:08.880 --> 00:23:13.650
of censorship to push domestic industries
and enable catch-up growth. Now there
00:23:13.650 --> 00:23:16.820
are a couple of further prerequisites.
First of all, the country needs to be
00:23:16.820 --> 00:23:20.640
large enough so that these
information intensive industries
00:23:20.640 --> 00:23:23.640
have a domestic market as well.
00:23:23.640 --> 00:23:27.379
Obviously. And then also only
targeted censorship can serve as
00:23:27.379 --> 00:23:32.159
protectionism. The only other way would be
if you decided on a domestic intranet and
00:23:32.159 --> 00:23:38.059
basically closed your entire intranet off
to the world. Which is kind of difficult.
00:23:38.059 --> 00:23:41.850
But what about the long-term effects
of that? Would they still be positive
00:23:41.850 --> 00:23:47.669
for the government? Now, I’m using
‘positive’ in a very… sort of something
00:23:47.669 --> 00:23:51.820
that should be taken with a grain of salt,
obviously. And what I did is I looked
00:23:51.820 --> 00:23:57.330
at China. Obviously, I’m a China watcher.
So I’m really interested in China. And
00:23:57.330 --> 00:24:02.190
this is kind of where my interest started.
And I’m really trying to find a framework
00:24:02.190 --> 00:24:07.219
where China isn’t the exception but
instead China kind of fits into the model.
00:24:07.219 --> 00:24:13.129
What we see is the Chinese government has
outsourced much if its censorship to these
00:24:13.129 --> 00:24:19.000
internet companies. Baidu, Sina weibo,
Tencent probably would not exist by now,
00:24:19.000 --> 00:24:24.820
actually, if the censorship didn’t exist.
And what we actually see now is that
00:24:24.820 --> 00:24:29.750
WeChat e.g. is going global. It has
more functionality than Whatsapp
00:24:29.750 --> 00:24:35.799
and they’re trying to get out. But as I’ll
be talking about later on a little bit
00:24:35.799 --> 00:24:41.810
the censorship is starting to be a problem
for these companies that used to benefit.
00:24:41.810 --> 00:24:46.840
There’s some things about Chinese… about
the character of Chinese Internet censorship
00:24:46.840 --> 00:24:54.409
that is relevant here. But what about
the future? Now first it’s difficult to
00:24:54.409 --> 00:24:58.660
innovate with this kind of censorship. And
this kind of insular education that we see
00:24:58.660 --> 00:25:03.450
also makes innovation, real innovation,
very difficult. In China e.g. Github
00:25:03.450 --> 00:25:07.631
is blocked most of the time. That makes
kind of collaborating, especially in
00:25:07.631 --> 00:25:11.730
coding environments, very, very hard.
00:25:11.730 --> 00:25:14.490
Second, we see more global internet enabled
00:25:14.490 --> 00:25:20.059
supply chains in the world. So if we have
these global Internet-enabled supply chains
00:25:20.059 --> 00:25:25.669
having internet censorship turns out to be
more of a disadvantage the more globalized
00:25:25.669 --> 00:25:31.879
these supply chains actually become. And
information becomes the most important
00:25:31.879 --> 00:25:36.230
commodity all throughout China. Now this
of course also makes Internet censorship
00:25:36.230 --> 00:25:41.000
more costly for the economy. What about
possible positives? So what could work
00:25:41.000 --> 00:25:45.500
in the Chinese government’s favour? First,
the Chinese intranet is actually pretty
00:25:45.500 --> 00:25:50.429
attractive to most people. Most people
don’t try to go outside, even like
00:25:50.429 --> 00:25:55.269
they don’t even know that they can’t. They
just don’t want to do it. Second, the IoT,
00:25:55.269 --> 00:25:59.429
where machines communicate with each other
doesn’t need to be affected because
00:25:59.429 --> 00:26:04.820
most of the censorship that we see
happening could be reworked in a way
00:26:04.820 --> 00:26:08.599
that doesn’t affect machine-to-machine
communication. And that wouldn’t be
00:26:08.599 --> 00:26:14.039
a problem for what the censorship intends
to do which is sort of suppress political
00:26:14.039 --> 00:26:20.669
opposition. And a third, the government
wants an economy more focused on domestic
00:26:20.669 --> 00:26:24.230
consumption. So if they want to do this
then censorship might actually be good
00:26:24.230 --> 00:26:30.669
for that. Now, for me, what I found out
when doing this research is first,
00:26:30.669 --> 00:26:34.709
standard economic models really aren’t
suited for this kind of question. Because
00:26:34.709 --> 00:26:38.370
they tend to use GDP, and I’ve told you
why GDP really is not a good measure
00:26:38.370 --> 00:26:43.419
for that. Second, the next step that
I’ll be doing is agent-based modeling.
00:26:43.419 --> 00:26:48.910
But I would really like to feed my models
with some reliable data. And I can’t
00:26:48.910 --> 00:26:53.400
really find any of that. I can find some
data going back a couple of years
00:26:53.400 --> 00:26:57.779
on, like, is there censorship, is there
no censorship. But I can’t really find any
00:26:57.779 --> 00:27:02.150
good data that distinguishes between
different types of censorship, which would
00:27:02.150 --> 00:27:06.440
be really important for the kind of
research that I really want to carry out
00:27:06.440 --> 00:27:11.610
in the future. Thank you, guys. If you
have questions you can ask now or
00:27:11.610 --> 00:27:15.129
you can come to me later, you can
of course also send me an e-mail.
00:27:15.129 --> 00:27:18.719
I’m always happy to talk about this topic.
00:27:18.719 --> 00:27:27.529
applause
00:27:27.529 --> 00:27:32.000
Herald: Thank you very much for this talk.
We have six microphones at the floor level
00:27:32.000 --> 00:27:35.660
here, so if you have questions we have
a very brief amount of time.
00:27:35.660 --> 00:27:40.430
Please line up at the microphones.
We have microphone no. 2 over here.
00:27:40.430 --> 00:27:46.480
Question: I want to mention one thing.
Always when talking about China censorship
00:27:46.480 --> 00:27:51.299
this censorship applies to China main
land. So it’s not Hong Kong and not Taiwan.
00:27:51.299 --> 00:27:51.959
Toni: Yes.
00:27:51.959 --> 00:27:55.769
Question: And my question I want
to ask is:
00:27:55.769 --> 00:27:59.219
What do you think about productivity
of work?
00:27:59.219 --> 00:28:05.200
So e.g. if you shut down Facebook do you
think this would increase working
00:28:05.200 --> 00:28:08.059
productivity?
Toni laughs
00:28:08.059 --> 00:28:13.010
applause
Toni: That’s a really interesting question,
00:28:13.010 --> 00:28:16.470
and something that I haven’t seen anywhere
in literature. There is a big literature
00:28:16.470 --> 00:28:21.970
discussion about what the internet as such
means for productivity, and that’s
00:28:21.970 --> 00:28:26.820
kind of both ways. Now, one of the things
to look at is that just because you
00:28:26.820 --> 00:28:31.200
shut down Facebook doesn’t mean you
shut down any sort of social network.
00:28:31.200 --> 00:28:36.389
And I do think that if people use Facebook
and suddenly aren’t able to use it anymore
00:28:36.389 --> 00:28:40.769
they would probably spend their resources
trying to find new ways to access Facebook
00:28:40.769 --> 00:28:48.790
which would probably not exactly
improve their productivity.
00:28:48.790 --> 00:28:52.299
Herald: Next question
from microphone no. 2.
00:28:52.299 --> 00:28:57.909
Question: Would it make sense to have
a model where firms use information
00:28:57.909 --> 00:29:02.480
as an input to a production function and
then model censorship as a kind of tax
00:29:02.480 --> 00:29:08.109
on that. That will seem like standard new
classical micro-econ one-on-one stuff?
00:29:08.109 --> 00:29:12.390
Toni: That would make sense. I’ve actually
looked at this. One of the problems with
00:29:12.390 --> 00:29:17.730
doing that is that information
as a commodity
00:29:17.730 --> 00:29:23.350
is very difficult to be used in this new
classical way because you usually assume
00:29:23.350 --> 00:29:28.020
that everything is kind of friction-less.
And if things are friction-less then
00:29:28.020 --> 00:29:31.619
information can’t really be a commodity
because you assume that information
00:29:31.619 --> 00:29:36.500
basically gets transferred immediately,
and without any sort of censorship. So
00:29:36.500 --> 00:29:39.590
we can talk about this a little bit later.
Maybe you have some ideas that
00:29:39.590 --> 00:29:43.740
I haven’t found yet.
It would be interesting.
00:29:43.740 --> 00:29:47.539
Herald: And the next question,
as well, from microphone no. 2.
00:29:47.539 --> 00:29:53.629
Question: So, going the same direction:
for GDP is rather defined what is
00:29:53.629 --> 00:29:59.429
the optimization problem for a government.
For your further approaches what would be
00:29:59.429 --> 00:30:05.279
the optimization that a government like
China does then. If you say e.g. Wikipedia
00:30:05.279 --> 00:30:08.950
which leaks out to all over the world but
what is the government optimizing then?
00:30:08.950 --> 00:30:15.049
Toni: What I’m looking at is economic welfare
as defined as producer and consumer surplus.
00:30:15.049 --> 00:30:22.539
And I assume that the government’s goal
is to optimize economic welfare for both
00:30:22.539 --> 00:30:27.519
producers, consumers and also for itself
as a producer and as a consumer.
00:30:27.519 --> 00:30:32.240
Question: So your criticism is more like
you don’t have a good proxy,
00:30:32.240 --> 00:30:33.870
using GDP for economic welfare?
00:30:33.870 --> 00:30:36.870
Toni: Yes, yes.
Okay. Thank you.
00:30:36.870 --> 00:30:38.370
Herald: I’m afraid we’re all out of time.
00:30:38.370 --> 00:30:40.350
Please give a warm round
of applause to Toni!
00:30:40.350 --> 00:30:43.690
applause
00:30:43.690 --> 00:30:46.260
post-roll music
00:30:46.260 --> 00:30:50.540
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