WEBVTT 00:00:00.420 --> 00:00:02.736 "When the crisis came, 00:00:02.736 --> 00:00:05.856 the serious limitations of existing economic 00:00:05.856 --> 00:00:10.908 and financial models immediately became apparent." 00:00:10.908 --> 00:00:15.890 "There is also a strong belief, which I share, 00:00:15.890 --> 00:00:20.889 that bad or oversimplistic and overconfident economics 00:00:20.889 --> 00:00:23.290 helped create the crisis." NOTE Paragraph 00:00:23.290 --> 00:00:25.557 Now, you've probably all heard of similar criticism 00:00:25.557 --> 00:00:28.899 coming from people who are skeptical of capitalism. 00:00:28.899 --> 00:00:30.576 But this is different. 00:00:30.576 --> 00:00:34.444 This is coming from the heart of finance. 00:00:34.444 --> 00:00:37.305 The first quote is from Jean-Claude Trichet 00:00:37.305 --> 00:00:41.180 when he was governor of the European Central Bank. 00:00:41.180 --> 00:00:43.419 The second quote is from the head 00:00:43.419 --> 00:00:46.784 of the U.K. Financial Services Authority. 00:00:46.784 --> 00:00:48.314 Are these people implying 00:00:48.314 --> 00:00:51.109 that we don't understand the economic systems 00:00:51.109 --> 00:00:54.249 that drive our modern societies? 00:00:54.249 --> 00:00:56.171 It gets worse. 00:00:56.171 --> 00:00:58.326 "We spend billions of dollars 00:00:58.326 --> 00:01:01.550 trying to understand the origins of the universe 00:01:01.550 --> 00:01:05.412 while we still don't understand the conditions 00:01:05.412 --> 00:01:14.138 for a stable society, a functioning economy, or peace." NOTE Paragraph 00:01:14.138 --> 00:01:16.973 What's happening here? How can this be possible? 00:01:16.973 --> 00:01:19.929 Do we really understand more about the fabric of reality 00:01:19.929 --> 00:01:21.592 than we do about the fabric 00:01:21.592 --> 00:01:24.730 which emerges from our human interactions? 00:01:24.730 --> 00:01:27.257 Unfortunately, the answer is yes. 00:01:27.257 --> 00:01:30.666 But there's an intriguing solution which is coming 00:01:30.666 --> 00:01:35.154 from what is known as the science of complexity. NOTE Paragraph 00:01:35.154 --> 00:01:37.997 To explain what this means and what this thing is, 00:01:37.997 --> 00:01:41.576 please let me quickly take a couple of steps back. 00:01:41.576 --> 00:01:43.966 I ended up in physics by accident. 00:01:43.966 --> 00:01:47.057 It was a random encounter when I was young, 00:01:47.057 --> 00:01:49.162 and since then, I've often wondered 00:01:49.162 --> 00:01:51.241 about the amazing success of physics 00:01:51.241 --> 00:01:55.608 in describing the reality we wake up in every day. 00:01:55.608 --> 00:01:58.904 In a nutshell, you can think of physics as follows. 00:01:58.904 --> 00:02:01.937 So you take a chunk of reality you want to understand 00:02:01.937 --> 00:02:05.706 and you translate it into mathematics. 00:02:05.706 --> 00:02:09.142 You encode it into equations. 00:02:09.142 --> 00:02:12.969 Then predictions can be made and tested. 00:02:12.969 --> 00:02:15.533 We're actually really lucky that this works, 00:02:15.533 --> 00:02:18.548 because no one really knows why the thoughts in our heads 00:02:18.548 --> 00:02:24.125 should actually relate to the fundamental workings of the universe. 00:02:24.125 --> 00:02:27.687 Despite the success, physics has its limits. 00:02:27.687 --> 00:02:30.409 As Dirk Helbing pointed out in the last quote, 00:02:30.409 --> 00:02:32.903 we don't really understand the complexity 00:02:32.903 --> 00:02:36.081 that relates to us, that surrounds us. 00:02:36.081 --> 00:02:40.729 This paradox is what got me interested in complex systems. 00:02:40.729 --> 00:02:42.633 So these are systems which are made up 00:02:42.633 --> 00:02:46.113 of many interconnected or interacting parts: 00:02:46.113 --> 00:02:49.927 swarms of birds or fish, ant colonies, 00:02:49.927 --> 00:02:53.361 ecosystems, brains, financial markets. 00:02:53.361 --> 00:02:57.687 These are just a few examples. 00:02:57.687 --> 00:03:02.930 Interestingly, complex systems are very hard to map 00:03:02.930 --> 00:03:04.790 into mathematical equations, 00:03:04.790 --> 00:03:09.283 so the usual physics approach doesn't really work here. NOTE Paragraph 00:03:09.283 --> 00:03:11.476 So what do we know about complex systems? 00:03:11.476 --> 00:03:15.418 Well, it turns out that what looks like complex behavior 00:03:15.418 --> 00:03:18.437 from the outside is actually the result 00:03:18.437 --> 00:03:22.634 of a few simple rules of interaction. 00:03:22.634 --> 00:03:26.859 This means you can forget about the equations 00:03:26.859 --> 00:03:28.722 and just start to understand the system 00:03:28.722 --> 00:03:31.426 by looking at the interactions, 00:03:31.426 --> 00:03:33.746 so you can actually forget about the equations 00:03:33.746 --> 00:03:36.219 and you just start to look at the interactions. 00:03:36.219 --> 00:03:39.456 And it gets even better, because most complex systems 00:03:39.456 --> 00:03:42.524 have this amazing property called emergence. 00:03:42.524 --> 00:03:44.930 So this means that the system as a whole 00:03:44.930 --> 00:03:46.665 suddenly starts to show a behavior 00:03:46.665 --> 00:03:49.809 which cannot be understood or predicted 00:03:49.809 --> 00:03:52.386 by looking at the components of the system. 00:03:52.386 --> 00:03:56.305 So the whole is literally more than the sum of its parts. 00:03:56.305 --> 00:03:58.651 And all of this also means that you can forget about 00:03:58.651 --> 00:04:04.000 the individual parts of the system, how complex they are. 00:04:04.000 --> 00:04:08.913 So if it's a cell or a termite or a bird, 00:04:08.913 --> 00:04:13.262 you just focus on the rules of interaction. NOTE Paragraph 00:04:13.262 --> 00:04:17.708 As a result, networks are ideal representations 00:04:17.708 --> 00:04:20.362 of complex systems. 00:04:20.362 --> 00:04:23.133 The nodes in the network 00:04:23.133 --> 00:04:25.892 are the system's components 00:04:25.892 --> 00:04:30.092 and the links are given by the interactions. 00:04:30.092 --> 00:04:32.917 So what equations are for physics, 00:04:32.917 --> 00:04:37.532 complex networks are for the study of complex systems. NOTE Paragraph 00:04:37.532 --> 00:04:40.756 This approach has been very successfully applied 00:04:40.756 --> 00:04:44.019 to many complex systems in physics, biology, 00:04:44.019 --> 00:04:47.260 computer science, the social sciences, 00:04:47.260 --> 00:04:49.557 but what about economics? 00:04:49.557 --> 00:04:51.975 Where are economic networks? 00:04:51.975 --> 00:04:56.572 This is a surprising and prominent gap in the literature. 00:04:56.572 --> 00:04:59.126 The study we published last year called 00:04:59.126 --> 00:05:02.452 "The Network of Global Corporate Control" 00:05:02.452 --> 00:05:08.382 was the first extensive analysis of economic networks. 00:05:08.382 --> 00:05:11.076 The study went viral on the Internet 00:05:11.076 --> 00:05:16.148 and it attracted a lot of attention from the international media. 00:05:16.148 --> 00:05:18.859 This is quite remarkable, because, again, 00:05:18.859 --> 00:05:20.280 why did no one look at this before? 00:05:20.280 --> 00:05:23.572 Similar data has been around for quite some time. NOTE Paragraph 00:05:23.572 --> 00:05:27.212 What we looked at in detail was ownership networks. 00:05:27.212 --> 00:05:32.652 So here the nodes are companies, people, governments, 00:05:32.652 --> 00:05:36.204 foundations, etc. 00:05:36.204 --> 00:05:39.032 And the links represent the shareholding relations, 00:05:39.032 --> 00:05:44.220 so Shareholder A has x percent of the shares in Company B. 00:05:44.220 --> 00:05:46.492 And we also assign a value to the company 00:05:46.492 --> 00:05:49.529 given by the operating revenue. 00:05:49.529 --> 00:05:52.628 So ownership networks reveal the patterns 00:05:52.628 --> 00:05:55.149 of shareholding relations. 00:05:55.149 --> 00:05:57.332 In this little example, you can see 00:05:57.332 --> 00:05:59.452 a few financial institutions 00:05:59.452 --> 00:06:03.845 with some of the many links highlighted. NOTE Paragraph 00:06:03.845 --> 00:06:06.525 Now you may think that no one's looked at this before 00:06:06.525 --> 00:06:08.861 because ownership networks are 00:06:08.861 --> 00:06:11.988 really, really boring to study. 00:06:11.988 --> 00:06:15.852 Well, as ownership is related to control, 00:06:15.852 --> 00:06:17.448 as I shall explain later, 00:06:17.448 --> 00:06:18.806 looking at ownership networks 00:06:18.806 --> 00:06:21.364 actually can give you answers to questions like, 00:06:21.364 --> 00:06:23.204 who are the key players? 00:06:23.204 --> 00:06:25.396 How are they organized? Are they isolated? 00:06:25.396 --> 00:06:26.884 Are they interconnected? 00:06:26.884 --> 00:06:30.759 And what is the overall distribution of control? 00:06:30.759 --> 00:06:34.235 In other words, who controls the world? 00:06:34.235 --> 00:06:36.604 I think this is an interesting question. NOTE Paragraph 00:06:36.604 --> 00:06:40.692 And it has implications for systemic risk. 00:06:40.692 --> 00:06:45.702 This is a measure of how vulnerable a system is overall. 00:06:45.702 --> 00:06:48.565 A high degree of interconnectivity 00:06:48.565 --> 00:06:51.432 can be bad for stability, 00:06:51.432 --> 00:06:54.876 because then the stress can spread through the system 00:06:54.876 --> 00:06:57.828 like an epidemic. NOTE Paragraph 00:06:57.828 --> 00:07:00.644 Scientists have sometimes criticized economists 00:07:00.644 --> 00:07:02.972 who believe ideas and concepts 00:07:02.972 --> 00:07:05.983 are more important than empirical data, 00:07:05.983 --> 00:07:09.132 because a foundational guideline in science is: 00:07:09.132 --> 00:07:12.468 Let the data speak. Okay. Let's do that. NOTE Paragraph 00:07:12.468 --> 00:07:15.062 So we started with a database containing 00:07:15.062 --> 00:07:19.205 13 million ownership relations from 2007. 00:07:19.205 --> 00:07:22.062 This is a lot of data, and because we wanted to find out 00:07:22.062 --> 00:07:24.620 who rules the world, 00:07:24.620 --> 00:07:28.452 we decided to focus on transnational corporations, 00:07:28.452 --> 00:07:29.800 or TNCs for short. 00:07:29.800 --> 00:07:33.396 These are companies that operate in more than one country, 00:07:33.396 --> 00:07:36.004 and we found 43,000. 00:07:36.004 --> 00:07:39.956 In the next step, we built the network around these companies, 00:07:39.956 --> 00:07:42.404 so we took all the TNCs' shareholders, 00:07:42.404 --> 00:07:44.496 and the shareholders' shareholders, etc., 00:07:44.496 --> 00:07:47.372 all the way upstream, and we did the same downstream, 00:07:47.372 --> 00:07:51.413 and ended up with a network containing 600,000 nodes 00:07:51.413 --> 00:07:52.842 and one million links. 00:07:52.842 --> 00:07:56.692 This is the TNC network which we analyzed. NOTE Paragraph 00:07:56.692 --> 00:07:59.220 And it turns out to be structured as follows. 00:07:59.220 --> 00:08:01.935 So you have a periphery and a center 00:08:01.935 --> 00:08:06.412 which contains about 75 percent of all the players, 00:08:06.412 --> 00:08:09.940 and in the center there's this tiny but dominant core 00:08:09.940 --> 00:08:14.764 which is made up of highly interconnected companies. 00:08:14.764 --> 00:08:17.199 To give you a better picture, 00:08:17.199 --> 00:08:18.810 think about a metropolitan area. 00:08:18.810 --> 00:08:21.101 So you have the suburbs and the periphery, 00:08:21.101 --> 00:08:23.798 you have a center like a financial district, 00:08:23.798 --> 00:08:25.541 then the core will be something like 00:08:25.541 --> 00:08:28.980 the tallest high rise building in the center. 00:08:28.980 --> 00:08:33.855 And we already see signs of organization going on here. 00:08:33.855 --> 00:08:39.588 Thirty-six percent of the TNCs are in the core only, 00:08:39.588 --> 00:08:43.959 but they make up 95 percent of the total operating revenue 00:08:43.959 --> 00:08:46.540 of all TNCs. NOTE Paragraph 00:08:46.540 --> 00:08:49.380 Okay, so now we analyzed the structure, 00:08:49.380 --> 00:08:52.942 so how does this relate to the control? 00:08:52.942 --> 00:08:56.869 Well, ownership gives voting rights to shareholders. 00:08:56.869 --> 00:08:59.588 This is the normal notion of control. 00:08:59.588 --> 00:09:02.795 And there are different models which allow you to compute 00:09:02.795 --> 00:09:05.576 the control you get from ownership. 00:09:05.576 --> 00:09:08.356 If you have more than 50 percent of the shares in a company, 00:09:08.356 --> 00:09:09.980 you get control, 00:09:09.980 --> 00:09:15.156 but usually it depends on the relative distribution of shares. 00:09:15.156 --> 00:09:18.045 And the network really matters. 00:09:18.045 --> 00:09:20.676 About 10 years ago, Mr. Tronchetti Provera 00:09:20.676 --> 00:09:24.080 had ownership and control in a small company, 00:09:24.080 --> 00:09:27.532 which had ownership and control in a bigger company. 00:09:27.532 --> 00:09:29.011 You get the idea. 00:09:29.011 --> 00:09:32.274 This ended up giving him control in Telecom Italia 00:09:32.274 --> 00:09:35.907 with a leverage of 26. 00:09:35.907 --> 00:09:39.850 So this means that, with each euro he invested, 00:09:39.850 --> 00:09:43.535 he was able to move 26 euros of market value 00:09:43.535 --> 00:09:46.911 through the chain of ownership relations. NOTE Paragraph 00:09:46.911 --> 00:09:49.991 Now what we actually computed in our study 00:09:49.991 --> 00:09:53.690 was the control over the TNCs' value. 00:09:53.690 --> 00:09:56.542 This allowed us to assign a degree of influence 00:09:56.542 --> 00:09:58.849 to each shareholder. 00:09:58.849 --> 00:10:01.431 This is very much in the sense of 00:10:01.431 --> 00:10:04.543 Max Weber's idea of potential power, 00:10:04.543 --> 00:10:08.355 which is the probability of imposing one's own will 00:10:08.355 --> 00:10:12.350 despite the opposition of others. NOTE Paragraph 00:10:12.350 --> 00:10:16.993 If you want to compute the flow in an ownership network, 00:10:16.993 --> 00:10:18.241 this is what you have to do. 00:10:18.241 --> 00:10:20.786 It's actually not that hard to understand. 00:10:20.786 --> 00:10:23.554 Let me explain by giving you this analogy. 00:10:23.554 --> 00:10:26.409 So think about water flowing in pipes 00:10:26.409 --> 00:10:29.591 where the pipes have different thickness. 00:10:29.591 --> 00:10:34.335 So similarly, the control is flowing in the ownership networks 00:10:34.335 --> 00:10:38.754 and is accumulating at the nodes. 00:10:38.754 --> 00:10:42.702 So what did we find after computing all this network control? 00:10:42.702 --> 00:10:48.089 Well, it turns out that the 737 top shareholders 00:10:48.089 --> 00:10:50.881 have the potential to collectively control 00:10:50.881 --> 00:10:55.141 80 percent of the TNCs' value. 00:10:55.141 --> 00:10:58.457 Now remember, we started out with 600,000 nodes, 00:10:58.457 --> 00:11:02.234 so these 737 top players 00:11:02.234 --> 00:11:06.057 make up a bit more than 0.1 percent. 00:11:06.057 --> 00:11:11.013 They're mostly financial institutions in the U.S. and the U.K. 00:11:11.013 --> 00:11:13.561 And it gets even more extreme. 00:11:13.561 --> 00:11:17.858 There are 146 top players in the core, 00:11:17.858 --> 00:11:22.078 and they together have the potential to collectively control 00:11:22.078 --> 00:11:27.433 40 percent of the TNCs' value. NOTE Paragraph 00:11:27.433 --> 00:11:30.229 What should you take home from all of this? 00:11:30.229 --> 00:11:33.817 Well, the high degree of control you saw 00:11:33.817 --> 00:11:38.707 is very extreme by any standard. 00:11:38.707 --> 00:11:41.257 The high degree of interconnectivity 00:11:41.257 --> 00:11:43.569 of the top players in the core 00:11:43.569 --> 00:11:48.746 could pose a significant systemic risk to the global economy 00:11:48.746 --> 00:11:52.466 and we could easily reproduce the TNC network 00:11:52.466 --> 00:11:54.417 with a few simple rules. 00:11:54.417 --> 00:11:56.897 This means that its structure is probably the result 00:11:56.897 --> 00:11:58.537 of self-organization. 00:11:58.537 --> 00:12:01.853 It's an emergent property which depends 00:12:01.853 --> 00:12:04.697 on the rules of interaction in the system, 00:12:04.697 --> 00:12:08.143 so it's probably not the result of a top-down approach 00:12:08.143 --> 00:12:11.569 like a global conspiracy. NOTE Paragraph 00:12:11.569 --> 00:12:14.502 Our study "is an impression of the moon's surface. 00:12:14.502 --> 00:12:15.831 It's not a street map." 00:12:15.831 --> 00:12:18.470 So you should take the exact numbers in our study 00:12:18.470 --> 00:12:19.910 with a grain of salt, 00:12:19.910 --> 00:12:23.302 yet it "gave us a tantalizing glimpse 00:12:23.302 --> 00:12:27.646 of a brave new world of finance." 00:12:27.646 --> 00:12:32.086 We hope to have opened the door for more such research in this direction, 00:12:32.086 --> 00:12:36.823 so the remaining unknown terrain will be charted in the future. 00:12:36.823 --> 00:12:38.268 And this is slowly starting. 00:12:38.268 --> 00:12:41.260 We're seeing the emergence of long-term 00:12:41.260 --> 00:12:44.830 and highly-funded programs which aim at understanding 00:12:44.830 --> 00:12:49.520 our networked world from a complexity point of view. 00:12:49.520 --> 00:12:51.558 But this journey has only just begun, 00:12:51.558 --> 00:12:56.996 so we will have to wait before we see the first results. NOTE Paragraph 00:12:56.996 --> 00:13:00.614 Now there is still a big problem, in my opinion. 00:13:00.614 --> 00:13:05.766 Ideas relating to finance, economics, politics, 00:13:05.766 --> 00:13:09.046 society, are very often tainted 00:13:09.046 --> 00:13:12.862 by people's personal ideologies. 00:13:12.862 --> 00:13:17.000 I really hope that this complexity perspective 00:13:17.000 --> 00:13:22.143 allows for some common ground to be found. 00:13:22.143 --> 00:13:25.062 It would be really great if it has the power 00:13:25.062 --> 00:13:30.125 to help end the gridlock created by conflicting ideas, 00:13:30.125 --> 00:13:35.255 which appears to be paralyzing our globalized world. 00:13:35.255 --> 00:13:39.921 Reality is so complex, we need to move away from dogma. 00:13:39.921 --> 00:13:42.807 But this is just my own personal ideology. NOTE Paragraph 00:13:42.807 --> 00:13:44.842 Thank you. NOTE Paragraph 00:13:44.842 --> 00:13:49.519 (Applause)