1
00:00:00,000 --> 00:00:13,149
33c3 pre-roll music
2
00:00:13,159 --> 00:00:15,269
Herald: Err ...
3
00:00:15,289 --> 00:00:17,820
H: ... a talk would be good, right?
4
00:00:18,290 --> 00:00:24,529
applause
5
00:00:26,169 --> 00:00:27,330
Do you want to give a talk?
6
00:00:27,340 --> 00:00:31,390
Toni: Aah, it’s a little early
but I’ll try.
7
00:00:31,390 --> 00:00:36,360
Herald: Okay, guys, well, I found someone
who’s willing to give a talk!
8
00:00:36,430 --> 00:00:41,820
laughter and applause
9
00:00:42,430 --> 00:00:47,010
That is most excellent.
So, if you ever asked yourself,
10
00:00:47,770 --> 00:00:53,120
I’ve got this big regime and
I’m rolling out internet censorship,
11
00:00:53,120 --> 00:00:56,449
what does my economy do?
12
00:00:56,449 --> 00:00:59,449
There are people in here
asking that question, right?
13
00:00:59,449 --> 00:01:02,750
There’s always someone at Congress
who’s asking some question.
14
00:01:02,760 --> 00:01:09,310
Well, you came to the right place,
and as part of her PhD thesis work
15
00:01:09,320 --> 00:01:15,030
Toni is going answer that question,
hopefully, to a satisfactory point.
16
00:01:15,030 --> 00:01:17,570
Please give a warm round of applause!
applause
17
00:01:17,580 --> 00:01:24,180
Toni!
ongoing applause
18
00:01:24,180 --> 00:01:27,520
Toni: Okay, thanks everyone for being
here, I hope you can all hear me
19
00:01:27,540 --> 00:01:32,590
correctly. And I’m glad to be here
and to be presenting
20
00:01:32,590 --> 00:01:36,109
some part of my thesis to day.
Now, this is ongoing work
21
00:01:36,109 --> 00:01:39,520
so I’m really grateful for any kind of feedback
that you guys would have
22
00:01:39,520 --> 00:01:43,300
and I’m really only presenting this
as kind of a first try,
23
00:01:43,300 --> 00:01:46,840
because when I looked at the topic
of internet censorship
24
00:01:46,840 --> 00:01:51,549
and what that could mean for an economy,
I really didn’t find anything academic
25
00:01:51,549 --> 00:01:56,280
and I was quite surprised: it seemed
like a very obvious question to me,
26
00:01:56,280 --> 00:02:00,979
because I was looking mostly
at China at the beginning.
27
00:02:00,979 --> 00:02:04,740
And I read a lot of newspaper articles
and I talked to a lot of businessmen
28
00:02:04,740 --> 00:02:08,060
who told me: “Well, doing business
in China is very difficult”
29
00:02:08,060 --> 00:02:11,020
and I think China is really
holding itself back by having
30
00:02:11,020 --> 00:02:15,400
this big censorship thing going.
31
00:02:15,400 --> 00:02:20,670
But no one really looked into
how it is holding itself back
32
00:02:20,670 --> 00:02:23,860
or if it is even holding itself back.
33
00:02:23,860 --> 00:02:26,940
So there is really
very, very little research.
34
00:02:26,940 --> 00:02:32,050
And we don’t even have an agreement among
economists or business studies people
35
00:02:32,050 --> 00:02:36,420
about what impact the internet has
on the economy. So if you want to ask:
36
00:02:36,420 --> 00:02:39,890
“So what does internet censorship do
to an economy?” it seems pretty obvious
37
00:02:39,890 --> 00:02:44,830
to first ask: “What does the internet do to
an economy?” and we don’t even know that.
38
00:02:44,830 --> 00:02:47,990
That was quite surprising to me and I’m
going to be talking about the reasons
39
00:02:47,990 --> 00:02:53,310
for that a little bit later on. But in
general, I was thinking of a research
40
00:02:53,310 --> 00:02:58,460
question to ask which for me is: “Does
internet censorship reduce economic welfare?”
41
00:02:58,460 --> 00:03:03,030
Now, not all of you are economists,
so some of you might think of welfare
42
00:03:03,030 --> 00:03:08,200
more as the transfer payments
that a state gives to its poorer people.
43
00:03:08,200 --> 00:03:12,800
But for economists, economic welfare
is defined as the consumer
44
00:03:12,800 --> 00:03:18,130
and producer surplus. So basically, the
difference between what something costs
45
00:03:18,130 --> 00:03:21,760
and what you can sell it for
is the producer surplus.
46
00:03:21,760 --> 00:03:25,160
The difference between
what you would be willing to pay
47
00:03:25,160 --> 00:03:28,250
and what you’re actually paying
is your consumer surplus.
48
00:03:28,250 --> 00:03:32,360
Now let’s assume I have a laptop
and I bought this.
49
00:03:32,360 --> 00:03:35,910
And I would have been willing to pay
€ 1500 for this laptop because
50
00:03:35,910 --> 00:03:39,860
I think it’s a very good product,
it’s by Lenovo that makes good laptops.
51
00:03:39,860 --> 00:03:44,260
But actually I got it for like €800
or €900. That would mean
52
00:03:44,260 --> 00:03:49,410
my personal consumer surplus
is something like €600 or €700.
53
00:03:49,410 --> 00:03:52,910
And if we add up everyone’s
individual consumer surplus
54
00:03:52,910 --> 00:03:58,840
we get the economic welfare surplus.
55
00:03:58,840 --> 00:04:02,660
So first, I was trying to figure out
what does the internet mean
56
00:04:02,660 --> 00:04:07,630
for the economy. And I’ve said that there
is really no good agreement on that.
57
00:04:07,630 --> 00:04:12,330
Now, a very crude measure that I found is
how much does "the Internet economy"
58
00:04:12,330 --> 00:04:17,780
contribute to GDP?
Now, what is "the internet economy"?
59
00:04:17,780 --> 00:04:22,280
It wasn’t very clear in the research
that I’ve read. It seems to be sort of
60
00:04:22,280 --> 00:04:27,620
online retail, and possibly some other
internet-enabled services?
61
00:04:27,620 --> 00:04:31,130
Possibly but not necessarily
internet advertisement revenue
62
00:04:31,130 --> 00:04:36,140
is reflected in this. But because it was
BCG, which is a big consulting agency
63
00:04:36,140 --> 00:04:40,870
that basically published this research
they weren’t very diligent about
64
00:04:40,870 --> 00:04:45,670
their methods, basically.
So we can see, well it seems that the UK
65
00:04:45,670 --> 00:04:49,720
has a pretty big part of internet economy
as part of GDP.
66
00:04:49,720 --> 00:04:53,760
That’s probably mostly because of
online retail which is bigger in the UK
67
00:04:53,760 --> 00:04:57,310
than in most other countries we look at.
And we see that there is
68
00:04:57,310 --> 00:05:01,680
a small difference between
developed and developing market averages
69
00:05:01,680 --> 00:05:06,980
when looking only at the G20 countries.
But this seems like a very
70
00:05:06,980 --> 00:05:10,330
dissatisfactory answer because first
of all, I don’t know the methods,
71
00:05:10,330 --> 00:05:12,870
so I can’t really say
whether this is actually good.
72
00:05:12,870 --> 00:05:16,350
And secondly, GDP is actually
not a good measure
73
00:05:16,350 --> 00:05:20,490
for what we are trying to measure because
a lot of the stuff that the internet creates,
74
00:05:20,490 --> 00:05:25,830
a lot of the value the internet creates
isn’t captured by GDP at all.
75
00:05:25,830 --> 00:05:30,310
One example is free online courses.
Most of the online courses you can take
76
00:05:30,310 --> 00:05:34,290
on the web are actually free.
And most of them are not ad-enabled.
77
00:05:34,290 --> 00:05:40,690
So most of them don’t really have
advertisements in the general sense.
78
00:05:40,690 --> 00:05:46,380
So classical economics basically says:
“Well, they don’t really create any value.”
79
00:05:46,380 --> 00:05:48,650
But if you’ve ever taken
one of these online courses,
80
00:05:48,650 --> 00:05:51,380
and maybe you’ve been lucky
and took a good one
81
00:05:51,380 --> 00:05:54,100
you would actually… I would say that
some of the courses I took,
82
00:05:54,100 --> 00:05:57,780
they created some value for me.
So one of the ways to look at this
83
00:05:57,780 --> 00:06:02,660
is actually to think about time as
something that has opportunity cost.
84
00:06:02,660 --> 00:06:06,180
So if I’m spending my time doing this
online course I’m not spending it
85
00:06:06,180 --> 00:06:11,030
e.g. earning money. I’m also not
spending it doing something leisurely
86
00:06:11,030 --> 00:06:17,749
that is fun for me.
And these guys, Brynjolfsson
87
00:06:17,749 --> 00:06:21,050
– I’m sorry I don’t know
how to pronounce it exactly,
88
00:06:21,050 --> 00:06:26,110
he sounds Swedish, possibly –
and ohh, in 2012
89
00:06:26,110 --> 00:06:33,020
they tried to get an idea of
how much consumer surplus
90
00:06:33,020 --> 00:06:38,950
these online courses actually create.
Which isn’t at all
91
00:06:38,950 --> 00:06:44,360
reflected in the GDP.
And you see that in some models
92
00:06:44,360 --> 00:06:49,550
it would be 5% of GDP
for these online courses alone.
93
00:06:49,550 --> 00:06:56,750
Even if we take their more... most conservative
model which is $4.18 billion
94
00:06:56,750 --> 00:06:59,729
on average for the years 2008-2011,
95
00:06:59,729 --> 00:07:03,890
that’s still a pretty significant chunk
of economic welfare
96
00:07:03,890 --> 00:07:07,780
that’s somehow being created
that is not reflected in GDP
97
00:07:07,780 --> 00:07:11,770
because GDP is only stuff
that you actually pay money for.
98
00:07:11,770 --> 00:07:14,919
Another example that we
might think of is Wikipedia.
99
00:07:14,919 --> 00:07:19,160
Now Wikipedia has a certain cost of
operating: obviously the servers and stuff.
100
00:07:19,160 --> 00:07:22,990
But because most people contributing
to Wikipedia are actually volunteers
101
00:07:22,990 --> 00:07:25,910
the cost of operating
does not really reflect
102
00:07:25,910 --> 00:07:30,250
the true value Wikipedia creates.
And one of the…
103
00:07:30,250 --> 00:07:32,860
even if you don’t want to say…
even if you don’t agree
104
00:07:32,860 --> 00:07:37,401
that time has opportunity cost, what
about the money that you don’t spend
105
00:07:37,401 --> 00:07:43,800
on encyclopedias? How many of you guys
have encyclopedias at home?
106
00:07:43,800 --> 00:07:46,210
OK, that’s more than I expected!
107
00:07:46,210 --> 00:07:49,260
How many of you guys have
recent encyclopedias at home?
108
00:07:49,260 --> 00:07:53,580
That’s a little less, this is kind of more
what I was expecting.
109
00:07:53,580 --> 00:07:57,880
And now, my family also… we also have
an encyclopedia at home.
110
00:07:57,880 --> 00:08:02,720
I think it’s from 1985 or something.
And before this encyclopedia
111
00:08:02,720 --> 00:08:06,210
we would regularly update an encyclopedia,
we would regularly go out and buy
112
00:08:06,210 --> 00:08:09,840
a new encyclopedia because
knowledge changed, obviously.
113
00:08:09,840 --> 00:08:14,410
But ever since probably 1990,
we just didn’t bother.
114
00:08:14,410 --> 00:08:20,630
So, assuming an encyclopedia might,
like a physical book, might cost €100.
115
00:08:20,630 --> 00:08:24,400
And assuming sort of 2/3
of all households in Germany
116
00:08:24,400 --> 00:08:28,100
have had an encyclopedia at one point.
117
00:08:28,100 --> 00:08:31,710
We’re looking at 13 million households
at this point.
118
00:08:31,710 --> 00:08:35,630
Now you don’t buy an encyclopedia
every year but you might buy it
119
00:08:35,630 --> 00:08:40,679
every ten years. So in order to simplify
this we can say, every year
120
00:08:40,679 --> 00:08:46,010
1.3 million households buy
an encyclopedia on average.
121
00:08:46,010 --> 00:08:52,680
1.3 million times €100,
so we’re at €130 million
122
00:08:52,680 --> 00:08:57,680
of economic welfare, of something that
people were willing to spend money for
123
00:08:57,680 --> 00:09:01,350
that they’re not spending money for anymore
because of Wikipedia, because now that
124
00:09:01,350 --> 00:09:05,930
we have Wikipedia most of the encyclopedias
aren’t actually useful for us anymore
125
00:09:05,930 --> 00:09:10,100
because the knowledge that we have,
the knowledge that they would have
126
00:09:10,100 --> 00:09:18,760
would be outdated very, very soon and
Wikipedia tends to be more up to date.
127
00:09:18,760 --> 00:09:23,550
Well, that was from the consumer’s side.
But what about the business side?
128
00:09:23,550 --> 00:09:29,319
There’s a lot of research on whether the
internet actually increases productivity
129
00:09:29,319 --> 00:09:33,500
for businesses or not. Well, I don’t really
want to go into that debate because
130
00:09:33,500 --> 00:09:38,209
it’s a really long tedious debate that is
kind of focused on “Well, you did this
131
00:09:38,209 --> 00:09:42,110
method wrong”, or “You did this wrong”,
and “Well, I don’t think your argument
132
00:09:42,110 --> 00:09:47,410
makes sense”. So it’s very… I don’t like
this kind of debate. I really like to go
133
00:09:47,410 --> 00:09:51,720
deeper in things. But one of the things
that I found was that a lot of businesses
134
00:09:51,720 --> 00:09:59,219
do rely on the internet by now. Now
we can see on this graph that most firms,
135
00:09:59,219 --> 00:10:06,199
overall about 70% of firms actually
use the email to communicate.
136
00:10:06,199 --> 00:10:09,550
Now email obviously only works
if you have internet, so they need
137
00:10:09,550 --> 00:10:16,450
some sort of access to internet in order
for their current business model to work.
138
00:10:16,450 --> 00:10:22,110
Now this was just some short ideas on
sort of what can the internet mean for
139
00:10:22,110 --> 00:10:26,149
the economy. And now I want to talk about
Internet censorship, just a little bit.
140
00:10:26,149 --> 00:10:33,620
Now, I’m not a censorship expert. I’m just
someone who read a lot of papers about it,
141
00:10:33,620 --> 00:10:37,660
and who was very interested in what kind
of effects this has beyond sort of
142
00:10:37,660 --> 00:10:43,890
the obvious “people don’t have access
to political information”.
143
00:10:43,890 --> 00:10:47,709
So first a definition. ‘Internet censorship’
is the controller suppression
144
00:10:47,709 --> 00:10:50,889
of what can be accessed, published
or viewed on the Internet
145
00:10:50,889 --> 00:10:55,269
enacted by regulators or on their own
initiative. Now, in trying to conceptualize
146
00:10:55,269 --> 00:10:59,269
internet censorship, for me, personally,
there’s two dimensions that are
147
00:10:59,269 --> 00:11:03,840
very important. One is how targeted
is this internet censorship?
148
00:11:03,840 --> 00:11:11,509
Now, you could, in theory, basically
have internet censorship
149
00:11:11,509 --> 00:11:15,339
that is very, very targeted,
which you see in some cases.
150
00:11:15,339 --> 00:11:18,729
Or you can have censorship
that isn’t targeted at all, like in Egypt.
151
00:11:18,729 --> 00:11:23,560
They just decided to close the internet
down, basically, for a day.
152
00:11:23,560 --> 00:11:28,249
That isn’t very targeted censorship,
obviously. The other thing to look at
153
00:11:28,249 --> 00:11:32,980
is how widespread is it? So if you are
a business or if you’re a normal consumer
154
00:11:32,980 --> 00:11:38,939
how probable is it that you would come (?)
something that’s censored?
155
00:11:38,939 --> 00:11:43,180
Now, obviously, if you’re in China it’s
a lot more probable that you would
156
00:11:43,180 --> 00:11:47,159
try to access something that’s censored
than if you’re in Germany. Even though
157
00:11:47,159 --> 00:11:52,720
Germany also does some censorship.
And the way I like to conceptualize it is
158
00:11:52,720 --> 00:11:58,019
to be kind of on a continuum. So I don’t
look… I don’t say “Well, either
159
00:11:58,019 --> 00:12:01,649
there’s censorship or there isn’t
censorship”. What I’m trying to say is
160
00:12:01,649 --> 00:12:06,930
“Censorship has a big spectrum
of things that can happen”.
161
00:12:06,930 --> 00:12:12,809
These are some types of Internet censorship
that have different sort of implications.
162
00:12:12,809 --> 00:12:16,309
I don’t want to go through them in detail
because I think we’ve heard some really
163
00:12:16,309 --> 00:12:21,540
interesting talks on Internet censorship
already. But this is kind of
164
00:12:21,540 --> 00:12:26,540
interesting or important for the model
that I’m trying to build.
165
00:12:26,540 --> 00:12:30,370
But before trying to build my model,
first some more motivation.
166
00:12:30,370 --> 00:12:33,980
I was trying to look at “is there any
evidence that it would have
167
00:12:33,980 --> 00:12:39,819
an economic impact?”. And there actually
is a study that’s conducted by sort of
168
00:12:39,819 --> 00:12:45,819
lobbying organizations, so obviously
should be taken with a grain of salt.
169
00:12:45,819 --> 00:12:50,310
But it is quite interesting, and it shows
that there seems to be a correlation
170
00:12:50,310 --> 00:12:59,499
between freedom and how good
the economic impact of internet is.
171
00:12:59,499 --> 00:13:03,769
This is just a simple correlation. You can
see that there’s a really good line
172
00:13:03,769 --> 00:13:09,920
going through it. They did do some
controlling for GDP per capita, so
173
00:13:09,920 --> 00:13:16,580
for development level. But it still seems
quite rudimentary, to be honest.
174
00:13:16,580 --> 00:13:23,979
The data that they use is quite bad
because it is very, very…
175
00:13:23,979 --> 00:13:30,289
it’s just not finally granular enough, and
a lot of it is kind of… someone rating…
176
00:13:30,289 --> 00:13:34,809
so “How do you think the economic…”,
“How do you think Internet
177
00:13:34,809 --> 00:13:39,699
impacts the economy in this country?”
And then this is the data that they use,
178
00:13:39,699 --> 00:13:48,069
to some degree. So it seemed very…
it didn’t really seem like a good, final answer.
179
00:13:48,069 --> 00:13:53,529
So I’m trying to set up my own model.
And in my model I have a government
180
00:13:53,529 --> 00:13:57,709
that chooses the type of censorship. And
for this type of censorship that it chooses
181
00:13:57,709 --> 00:14:02,509
it pays a cost. Because we all know
censorship can be very expensive.
182
00:14:02,509 --> 00:14:09,709
And in my model for now the only type of
expenses that I calculate are actual
183
00:14:09,709 --> 00:14:16,989
manpower and technology expenses. I don’t
calculate reputation expenses at this point.
184
00:14:16,989 --> 00:14:24,209
There is… there are firms in n industries.
Now this n is kind of not a fixed number
185
00:14:24,209 --> 00:14:30,629
but instead is a number that can fluctuate
depending on the kind of country
186
00:14:30,629 --> 00:14:37,879
I’m trying to model. And these industries
distinguish themselves by their
187
00:14:37,879 --> 00:14:42,459
information intensity, or what I like
to call ‘information intensity’. Basically
188
00:14:42,459 --> 00:14:47,540
I look at information as a commodity.
And what I’m trying to decide, or
189
00:14:47,540 --> 00:14:51,910
the way I distinguish different kinds of
industry is how important is information
190
00:14:51,910 --> 00:14:56,279
as a commodity, as opposed to other kinds
of commodities that are important
191
00:14:56,279 --> 00:15:01,160
for this industry. So let’s look at
information intensity equals Zero.
192
00:15:01,160 --> 00:15:05,259
Like if we don’t really… if information
as a commodity really isn’t important,
193
00:15:05,259 --> 00:15:09,720
especially sort of conveyed information,
transmitted information. We can
194
00:15:09,720 --> 00:15:14,309
think of traditional agriculture. Now
I know today’s agriculture tends to be
195
00:15:14,309 --> 00:15:18,859
large-scale, and there’s a lot of
technology involved. But if you look at
196
00:15:18,859 --> 00:15:24,170
very traditional agriculture that we
still might see happening in some parts
197
00:15:24,170 --> 00:15:30,060
of Africa there usually is very, very
little information transmission involved.
198
00:15:30,060 --> 00:15:34,069
And most of the information transmission
that is involved is actually mostly through
199
00:15:34,069 --> 00:15:40,189
word of mouth. So that would be a case of
information intensity of very close to Zero.
200
00:15:40,189 --> 00:15:43,790
And then if we look at information intensity
of 1 where basically the internet is
201
00:15:43,790 --> 00:15:48,759
the most… or information is the most
important commodity. Internet businesses
202
00:15:48,759 --> 00:15:54,839
themselves would… obviously qualify here,
– sorry – like, let’s look at Facebook
203
00:15:54,839 --> 00:15:59,899
and other kinds of businesses like this.
And in between we have sort of industrial
204
00:15:59,899 --> 00:16:03,339
companies in the modern world.
Now if we’re closer to the Zero end
205
00:16:03,339 --> 00:16:07,639
of the spectrum we might be
at 0.2 .. 0.3, something like this,
206
00:16:07,639 --> 00:16:15,449
we might be in traditional garment
factories. They do have information needs,
207
00:16:15,449 --> 00:16:20,720
they get their cuts and stuff from the
Internet by now, or by email.
208
00:16:20,720 --> 00:16:25,129
But once they have them they basically stay
the same for a couple of weeks or months.
209
00:16:25,129 --> 00:16:30,409
So there’s a very low information
requirement. On the other side,
210
00:16:30,409 --> 00:16:35,999
closer to 0.8 or something
like that we have high-tech,
211
00:16:35,999 --> 00:16:41,220
especially software manufacturing,
so to speak. Information and being able
212
00:16:41,220 --> 00:16:44,930
to transmit this information is very
important. Now, in between we might look
213
00:16:44,930 --> 00:16:51,259
at traditional industrial companies
like automobile manufacturing
214
00:16:51,259 --> 00:16:56,000
that might be somewhere in between.
And before the game, or before…
215
00:16:56,000 --> 00:17:00,160
or at the first run of the model
‘service level’ and ‘globalization level’
216
00:17:00,160 --> 00:17:05,599
are randomly distributed. The information
intensity of industries is also kind of
217
00:17:05,599 --> 00:17:11,799
randomly distributed, but not in a true
random fashion. Because when looking
218
00:17:11,799 --> 00:17:15,500
in the wild, sort of what kind of
economies exist, most of them…
219
00:17:15,500 --> 00:17:19,199
the information intensity of one
industry is kind of correlated with
220
00:17:19,199 --> 00:17:23,449
information intensities of other industries
in this country. Like in Germany
221
00:17:23,449 --> 00:17:29,269
we’re very known for a certain type
of industry that we have quite a lot of,
222
00:17:29,269 --> 00:17:35,440
which is manufacturing, very high-technology
manufacturing. So we have more industries
223
00:17:35,440 --> 00:17:40,450
in this area but we have less traditional
agriculture, for example.
224
00:17:40,450 --> 00:17:44,669
So having a true random distribution
wouldn’t work. In addition the service level
225
00:17:44,669 --> 00:17:49,919
and the globalization level are randomly
distributed as kind of external variables.
226
00:17:49,919 --> 00:17:55,090
Obviously, this is a simplification because
I can’t really start at the beginning like
227
00:17:55,090 --> 00:17:58,870
I can’t say: “Oh well, I’ll start,
I don’t know, 2000 BC
228
00:17:58,870 --> 00:18:04,190
with a very blank economy, and then
something happens and something happens
229
00:18:04,190 --> 00:18:08,320
and something happens”. That’s just not
realistic. So in order to get a better idea
230
00:18:08,320 --> 00:18:12,830
of what happens with different types of
economies, what I’m doing is I’m running
231
00:18:12,830 --> 00:18:18,899
this game or this model again and again.
And having these random parameters
232
00:18:18,899 --> 00:18:24,539
basically changed everytime.
So on average there should be…
233
00:18:24,539 --> 00:18:29,289
there should be usable results.
234
00:18:29,289 --> 00:18:35,230
Now what this is actually missing
is the consumer as a labourer.
235
00:18:35,230 --> 00:18:40,090
So I don’t really have ‘labour’ reflected
in here. A more complete model would have
236
00:18:40,090 --> 00:18:44,080
that reflected. But it’s not the most
interesting aspect of my model, so
237
00:18:44,080 --> 00:18:49,940
I’m not presenting this here, basically.
238
00:18:49,940 --> 00:18:56,080
Now, let’s look at what this would
mean for firms. In my model
239
00:18:56,080 --> 00:18:59,649
what kind of things would I expect
thinking through it logically which is
240
00:18:59,649 --> 00:19:04,820
always the first step when trying to model
something. First of all if we have
241
00:19:04,820 --> 00:19:10,130
an information intensity of something
greater than Zero but smaller than One.
242
00:19:10,130 --> 00:19:14,410
Because the information intensity being
close to One is kind of a special case
243
00:19:14,410 --> 00:19:18,520
that I’ll be talking about later on.
Internet censorship increases the cost
244
00:19:18,520 --> 00:19:22,360
and uncertainty of information.
And of course that is more important
245
00:19:22,360 --> 00:19:27,850
the more important information is
for this certain industry.
246
00:19:27,850 --> 00:19:33,850
So for a traditional garment factory
internet censorship might be a lot
247
00:19:33,850 --> 00:19:41,000
less important than for a semiconductor
factory that has to receive
248
00:19:41,000 --> 00:19:47,090
new blueprints every day or every month
or something. The second thing is
249
00:19:47,090 --> 00:19:51,559
the more globalized the economy as a whole
is the more costly internet censorship
250
00:19:51,559 --> 00:19:58,490
will be. Similar reasoning.
251
00:19:58,490 --> 00:20:02,990
And another thing for firms is the
less focused the censorship
252
00:20:02,990 --> 00:20:07,640
the higher the cost. Now this assumes that
the censorship or the goal of censorship
253
00:20:07,640 --> 00:20:14,370
usually isn’t to turn down firms or to
make sure that firms don’t succeed.
254
00:20:14,370 --> 00:20:19,820
So if censorship is very focused
firms tend to be affected less
255
00:20:19,820 --> 00:20:25,149
which makes their associated cost less.
Now of course we can argue, well,
256
00:20:25,149 --> 00:20:29,399
firms can circumvent censorship, and they
can do that for sure. But it is expensive
257
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
258
00:20:35,299 --> 00:20:40,919
is expensive. Then, having someone sort of
make sure that the VPN works is expensive,
259
00:20:40,919 --> 00:20:44,009
every couple of months you need to change
it because the Chinese Government decides,
260
00:20:44,009 --> 00:20:52,549
well, this VPN shouldn’t work anymore. So
it’s a very expensive and uncertain thing,
261
00:20:52,549 --> 00:20:57,909
really. For firms in
‘information intensity = 1’
262
00:20:57,909 --> 00:21:02,940
it obviously also increases the cost
of operating. Some of these firms actually
263
00:21:02,940 --> 00:21:07,970
carry out some censorship for governments.
We have seen that happening more recently.
264
00:21:07,970 --> 00:21:12,570
But there might actually be some firms
that have a relative advantage, especially
265
00:21:12,570 --> 00:21:16,820
domestic firms often have a relative
advantage due to the censorship because
266
00:21:16,820 --> 00:21:20,950
they know the regulators better, they know
how to deal with it, they might have
267
00:21:20,950 --> 00:21:25,039
less need to circumvent, actually.
And even if they do need to circumvent
268
00:21:25,039 --> 00:21:29,539
it’s easier for them because
they speak the language etc.
269
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.
270
00:21:34,090 --> 00:21:38,460
For the government – I’ve said
that censorship is costly. But moreover,
271
00:21:38,460 --> 00:21:43,100
the more targeted and accurate censorship
is the more manpower and technology intensive
272
00:21:43,100 --> 00:21:50,389
it actually is. This is a finding by
Leberknight et al. in a research paper.
273
00:21:50,389 --> 00:21:54,480
I think they’re electrical engineers, and
they calculated through different types
274
00:21:54,480 --> 00:22:00,350
of censorships and how expensive it would
be to scale them up. So that is actually
275
00:22:00,350 --> 00:22:03,479
a really interesting finding because
it shows that for governments
276
00:22:03,479 --> 00:22:10,460
having sort of less targeted censorship
is less costly. But this is the kind of
277
00:22:10,460 --> 00:22:17,039
censorship that is actually most affecting
in a negative way to firms,
278
00:22:17,039 --> 00:22:20,990
in an economy. So that’s kind of not
a result that we would really want
279
00:22:20,990 --> 00:22:24,919
because the incentives don’t line up in
that way. And economists love to talk
280
00:22:24,919 --> 00:22:29,169
about incentives, obviously. Now for
consumers, they would obviously get
281
00:22:29,169 --> 00:22:33,090
less benefits through the internet, the
benefits that I’ve talked about before.
282
00:22:33,090 --> 00:22:38,430
And also businesses often pass on the cost
to consumers.
283
00:22:38,430 --> 00:22:43,350
Now however, some countries
still benefit from internet censorship.
284
00:22:43,350 --> 00:22:45,970
I’ve talked mostly
about why it’s costly to do it,
285
00:22:45,970 --> 00:22:48,700
and I think it is costly in most cases.
286
00:22:48,700 --> 00:22:53,210
But developing countries that start out at
low service and low globalization levels
287
00:22:53,210 --> 00:22:58,950
usually have… in these kind of situations
internet censorship has less of an impact,
288
00:22:58,950 --> 00:23:04,370
less of a negative impact.
And censorship can actually act
289
00:23:04,370 --> 00:23:08,880
as protectionism. In information intensive
industries governments can use this kind
290
00:23:08,880 --> 00:23:13,650
of censorship to push domestic industries
and enable catch-up growth. Now there
291
00:23:13,650 --> 00:23:16,820
are a couple of further prerequisites.
First of all, the country needs to be
292
00:23:16,820 --> 00:23:20,640
large enough so that these
information intensive industries
293
00:23:20,640 --> 00:23:23,640
have a domestic market as well.
294
00:23:23,640 --> 00:23:27,379
Obviously. And then also only
targeted censorship can serve as
295
00:23:27,379 --> 00:23:32,159
protectionism. The only other way would be
if you decided on a domestic intranet and
296
00:23:32,159 --> 00:23:38,059
basically closed your entire intranet off
to the world. Which is kind of difficult.
297
00:23:38,059 --> 00:23:41,850
But what about the long-term effects
of that? Would they still be positive
298
00:23:41,850 --> 00:23:47,669
for the government? Now, I’m using
‘positive’ in a very… sort of something
299
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
300
00:23:51,820 --> 00:23:57,330
at China. Obviously, I’m a China watcher.
So I’m really interested in China. And
301
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
302
00:24:02,190 --> 00:24:07,219
where China isn’t the exception but
instead China kind of fits into the model.
303
00:24:07,219 --> 00:24:13,129
What we see is the Chinese government has
outsourced much if its censorship to these
304
00:24:13,129 --> 00:24:19,000
internet companies. Baidu, Sina weibo,
Tencent probably would not exist by now,
305
00:24:19,000 --> 00:24:24,820
actually, if the censorship didn’t exist.
And what we actually see now is that
306
00:24:24,820 --> 00:24:29,750
WeChat e.g. is going global. It has
more functionality than Whatsapp
307
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
308
00:24:35,799 --> 00:24:41,810
the censorship is starting to be a problem
for these companies that used to benefit.
309
00:24:41,810 --> 00:24:46,840
There’s some things about Chinese… about
the character of Chinese Internet censorship
310
00:24:46,840 --> 00:24:54,409
that is relevant here. But what about
the future? Now first it’s difficult to
311
00:24:54,409 --> 00:24:58,660
innovate with this kind of censorship. And
this kind of insular education that we see
312
00:24:58,660 --> 00:25:03,450
also makes innovation, real innovation,
very difficult. In China e.g. Github
313
00:25:03,450 --> 00:25:07,631
is blocked most of the time. That makes
kind of collaborating, especially in
314
00:25:07,631 --> 00:25:11,730
coding environments, very, very hard.
315
00:25:11,730 --> 00:25:14,490
Second, we see more global internet enabled
316
00:25:14,490 --> 00:25:20,059
supply chains in the world. So if we have
these global Internet-enabled supply chains
317
00:25:20,059 --> 00:25:25,669
having internet censorship turns out to be
more of a disadvantage the more globalized
318
00:25:25,669 --> 00:25:31,879
these supply chains actually become. And
information becomes the most important
319
00:25:31,879 --> 00:25:36,230
commodity all throughout China. Now this
of course also makes Internet censorship
320
00:25:36,230 --> 00:25:41,000
more costly for the economy. What about
possible positives? So what could work
321
00:25:41,000 --> 00:25:45,500
in the Chinese government’s favour? First,
the Chinese intranet is actually pretty
322
00:25:45,500 --> 00:25:50,429
attractive to most people. Most people
don’t try to go outside, even like
323
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,
324
00:25:55,269 --> 00:25:59,429
where machines communicate with each other
doesn’t need to be affected because
325
00:25:59,429 --> 00:26:04,820
most of the censorship that we see
happening could be reworked in a way
326
00:26:04,820 --> 00:26:08,599
that doesn’t affect machine-to-machine
communication. And that wouldn’t be
327
00:26:08,599 --> 00:26:14,039
a problem for what the censorship intends
to do which is sort of suppress political
328
00:26:14,039 --> 00:26:20,669
opposition. And a third, the government
wants an economy more focused on domestic
329
00:26:20,669 --> 00:26:24,230
consumption. So if they want to do this
then censorship might actually be good
330
00:26:24,230 --> 00:26:30,669
for that. Now, for me, what I found out
when doing this research is first,
331
00:26:30,669 --> 00:26:34,709
standard economic models really aren’t
suited for this kind of question. Because
332
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
333
00:26:38,370 --> 00:26:43,419
for that. Second, the next step that
I’ll be doing is agent-based modeling.
334
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
335
00:26:48,910 --> 00:26:53,400
really find any of that. I can find some
data going back a couple of years
336
00:26:53,400 --> 00:26:57,779
on, like, is there censorship, is there
no censorship. But I can’t really find any
337
00:26:57,779 --> 00:27:02,150
good data that distinguishes between
different types of censorship, which would
338
00:27:02,150 --> 00:27:06,440
be really important for the kind of
research that I really want to carry out
339
00:27:06,440 --> 00:27:11,610
in the future. Thank you, guys. If you
have questions you can ask now or
340
00:27:11,610 --> 00:27:15,129
you can come to me later, you can
of course also send me an e-mail.
341
00:27:15,129 --> 00:27:18,719
I’m always happy to talk about this topic.
342
00:27:18,719 --> 00:27:27,529
applause
343
00:27:27,529 --> 00:27:32,000
Herald: Thank you very much for this talk.
We have six microphones at the floor level
344
00:27:32,000 --> 00:27:35,660
here, so if you have questions we have
a very brief amount of time.
345
00:27:35,660 --> 00:27:40,430
Please line up at the microphones.
We have microphone no. 2 over here.
346
00:27:40,430 --> 00:27:46,480
Question: I want to mention one thing.
Always when talking about China censorship
347
00:27:46,480 --> 00:27:51,299
this censorship applies to China main
land. So it’s not Hong Kong and not Taiwan.
348
00:27:51,299 --> 00:27:51,959
Toni: Yes.
349
00:27:51,959 --> 00:27:55,769
Question: And my question I want
to ask is:
350
00:27:55,769 --> 00:27:59,219
What do you think about productivity
of work?
351
00:27:59,219 --> 00:28:05,200
So e.g. if you shut down Facebook do you
think this would increase working
352
00:28:05,200 --> 00:28:08,059
productivity?
Toni laughs
353
00:28:08,059 --> 00:28:13,010
applause
Toni: That’s a really interesting question,
354
00:28:13,010 --> 00:28:16,470
and something that I haven’t seen anywhere
in literature. There is a big literature
355
00:28:16,470 --> 00:28:21,970
discussion about what the internet as such
means for productivity, and that’s
356
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
357
00:28:26,820 --> 00:28:31,200
shut down Facebook doesn’t mean you
shut down any sort of social network.
358
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
359
00:28:36,389 --> 00:28:40,769
they would probably spend their resources
trying to find new ways to access Facebook
360
00:28:40,769 --> 00:28:48,790
which would probably not exactly
improve their productivity.
361
00:28:48,790 --> 00:28:52,299
Herald: Next question
from microphone no. 2.
362
00:28:52,299 --> 00:28:57,909
Question: Would it make sense to have
a model where firms use information
363
00:28:57,909 --> 00:29:02,480
as an input to a production function and
then model censorship as a kind of tax
364
00:29:02,480 --> 00:29:08,109
on that. That will seem like standard new
classical micro-econ one-on-one stuff?
365
00:29:08,109 --> 00:29:12,390
Toni: That would make sense. I’ve actually
looked at this. One of the problems with
366
00:29:12,390 --> 00:29:17,730
doing that is that information
as a commodity
367
00:29:17,730 --> 00:29:23,350
is very difficult to be used in this new
classical way because you usually assume
368
00:29:23,350 --> 00:29:28,020
that everything is kind of friction-less.
And if things are friction-less then
369
00:29:28,020 --> 00:29:31,619
information can’t really be a commodity
because you assume that information
370
00:29:31,619 --> 00:29:36,500
basically gets transferred immediately,
and without any sort of censorship. So
371
00:29:36,500 --> 00:29:39,590
we can talk about this a little bit later.
Maybe you have some ideas that
372
00:29:39,590 --> 00:29:43,740
I haven’t found yet.
It would be interesting.
373
00:29:43,740 --> 00:29:47,539
Herald: And the next question,
as well, from microphone no. 2.
374
00:29:47,539 --> 00:29:53,629
Question: So, going the same direction:
for GDP is rather defined what is
375
00:29:53,629 --> 00:29:59,429
the optimization problem for a government.
For your further approaches what would be
376
00:29:59,429 --> 00:30:05,279
the optimization that a government like
China does then. If you say e.g. Wikipedia
377
00:30:05,279 --> 00:30:08,950
which leaks out to all over the world but
what is the government optimizing then?
378
00:30:08,950 --> 00:30:15,049
Toni: What I’m looking at is economic welfare
as defined as producer and consumer surplus.
379
00:30:15,049 --> 00:30:22,539
And I assume that the government’s goal
is to optimize economic welfare for both
380
00:30:22,539 --> 00:30:27,519
producers, consumers and also for itself
as a producer and as a consumer.
381
00:30:27,519 --> 00:30:32,240
Question: So your criticism is more like
you don’t have a good proxy,
382
00:30:32,240 --> 00:30:33,870
using GDP for economic welfare?
383
00:30:33,870 --> 00:30:36,870
Toni: Yes, yes.
Okay. Thank you.
384
00:30:36,870 --> 00:30:38,370
Herald: I’m afraid we’re all out of time.
385
00:30:38,370 --> 00:30:40,350
Please give a warm round
of applause to Toni!
386
00:30:40,350 --> 00:30:43,690
applause
387
00:30:43,690 --> 00:30:46,260
post-roll music
388
00:30:46,260 --> 00:30:50,540
Subtitles created by c3subtitles.de
in the year 2017. Join, and help us!