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!*