Who controls the world?
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0:00 - 0:03"When the crisis came,
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0:03 - 0:06the serious limitations of existing economic
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0:06 - 0:11and financial models immediately became apparent."
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0:11 - 0:16"There is also a strong belief, which I share,
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0:16 - 0:21that bad or oversimplistic and overconfident economics
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0:21 - 0:23helped create the crisis."
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0:23 - 0:26Now, you've probably all heard of similar criticism
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0:26 - 0:29coming from people who are skeptical of capitalism.
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0:29 - 0:31But this is different.
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0:31 - 0:34This is coming from the heart of finance.
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0:34 - 0:37The first quote is from Jean-Claude Trichet
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0:37 - 0:41when he was governor of the European Central Bank.
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0:41 - 0:43The second quote is from the head
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0:43 - 0:47of the U.K. Financial Services Authority.
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0:47 - 0:48Are these people implying
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0:48 - 0:51that we don't understand the economic systems
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0:51 - 0:54that drive our modern societies?
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0:54 - 0:56It gets worse.
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0:56 - 0:58"We spend billions of dollars
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0:58 - 1:02trying to understand the origins of the universe
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1:02 - 1:05while we still don't understand the conditions
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1:05 - 1:14for a stable society, a functioning economy, or peace."
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1:14 - 1:17What's happening here? How can this be possible?
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1:17 - 1:20Do we really understand more about the fabric of reality
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1:20 - 1:22than we do about the fabric
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1:22 - 1:25which emerges from our human interactions?
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1:25 - 1:27Unfortunately, the answer is yes.
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1:27 - 1:31But there's an intriguing solution which is coming
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1:31 - 1:35from what is known as the science of complexity.
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1:35 - 1:38To explain what this means and what this thing is,
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1:38 - 1:42please let me quickly take a couple of steps back.
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1:42 - 1:44I ended up in physics by accident.
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1:44 - 1:47It was a random encounter when I was young,
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1:47 - 1:49and since then, I've often wondered
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1:49 - 1:51about the amazing success of physics
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1:51 - 1:56in describing the reality we wake up in every day.
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1:56 - 1:59In a nutshell, you can think of physics as follows.
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1:59 - 2:02So you take a chunk of reality you want to understand
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2:02 - 2:06and you translate it into mathematics.
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2:06 - 2:09You encode it into equations.
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2:09 - 2:13Then predictions can be made and tested.
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2:13 - 2:16We're actually really lucky that this works,
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2:16 - 2:19because no one really knows why the thoughts in our heads
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2:19 - 2:24should actually relate to the fundamental workings of the universe.
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2:24 - 2:28Despite the success, physics has its limits.
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2:28 - 2:30As Dirk Helbing pointed out in the last quote,
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2:30 - 2:33we don't really understand the complexity
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2:33 - 2:36that relates to us, that surrounds us.
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2:36 - 2:41This paradox is what got me interested in complex systems.
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2:41 - 2:43So these are systems which are made up
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2:43 - 2:46of many interconnected or interacting parts:
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2:46 - 2:50swarms of birds or fish, ant colonies,
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2:50 - 2:53ecosystems, brains, financial markets.
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2:53 - 2:58These are just a few examples.
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2:58 - 3:03Interestingly, complex systems are very hard to map
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3:03 - 3:05into mathematical equations,
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3:05 - 3:09so the usual physics approach doesn't really work here.
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3:09 - 3:11So what do we know about complex systems?
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3:11 - 3:15Well, it turns out that what looks like complex behavior
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3:15 - 3:18from the outside is actually the result
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3:18 - 3:23of a few simple rules of interaction.
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3:23 - 3:27This means you can forget about the equations
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3:27 - 3:29and just start to understand the system
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3:29 - 3:31by looking at the interactions,
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3:31 - 3:34so you can actually forget about the equations
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3:34 - 3:36and you just start to look at the interactions.
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3:36 - 3:39And it gets even better, because most complex systems
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3:39 - 3:43have this amazing property called emergence.
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3:43 - 3:45So this means that the system as a whole
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3:45 - 3:47suddenly starts to show a behavior
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3:47 - 3:50which cannot be understood or predicted
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3:50 - 3:52by looking at the components of the system.
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3:52 - 3:56So the whole is literally more than the sum of its parts.
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3:56 - 3:59And all of this also means that you can forget about
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3:59 - 4:04the individual parts of the system, how complex they are.
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4:04 - 4:09So if it's a cell or a termite or a bird,
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4:09 - 4:13you just focus on the rules of interaction.
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4:13 - 4:18As a result, networks are ideal representations
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4:18 - 4:20of complex systems.
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4:20 - 4:23The nodes in the network
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4:23 - 4:26are the system's components
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4:26 - 4:30and the links are given by the interactions.
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4:30 - 4:33So what equations are for physics,
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4:33 - 4:38complex networks are for the study of complex systems.
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4:38 - 4:41This approach has been very successfully applied
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4:41 - 4:44to many complex systems in physics, biology,
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4:44 - 4:47computer science, the social sciences,
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4:47 - 4:50but what about economics?
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4:50 - 4:52Where are economic networks?
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4:52 - 4:57This is a surprising and prominent gap in the literature.
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4:57 - 4:59The study we published last year called
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4:59 - 5:02"The Network of Global Corporate Control"
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5:02 - 5:08was the first extensive analysis of economic networks.
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5:08 - 5:11The study went viral on the Internet
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5:11 - 5:16and it attracted a lot of attention from the international media.
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5:16 - 5:19This is quite remarkable, because, again,
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5:19 - 5:20why did no one look at this before?
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5:20 - 5:24Similar data has been around for quite some time.
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5:24 - 5:27What we looked at in detail was ownership networks.
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5:27 - 5:33So here the nodes are companies, people, governments,
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5:33 - 5:36foundations, etc.
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5:36 - 5:39And the links represent the shareholding relations,
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5:39 - 5:44so Shareholder A has x percent of the shares in Company B.
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5:44 - 5:46And we also assign a value to the company
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5:46 - 5:50given by the operating revenue.
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5:50 - 5:53So ownership networks reveal the patterns
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5:53 - 5:55of shareholding relations.
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5:55 - 5:57In this little example, you can see
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5:57 - 5:59a few financial institutions
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5:59 - 6:04with some of the many links highlighted.
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6:04 - 6:07Now you may think that no one's looked at this before
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6:07 - 6:09because ownership networks are
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6:09 - 6:12really, really boring to study.
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6:12 - 6:16Well, as ownership is related to control,
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6:16 - 6:17as I shall explain later,
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6:17 - 6:19looking at ownership networks
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6:19 - 6:21actually can give you answers to questions like,
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6:21 - 6:23who are the key players?
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6:23 - 6:25How are they organized? Are they isolated?
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6:25 - 6:27Are they interconnected?
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6:27 - 6:31And what is the overall distribution of control?
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6:31 - 6:34In other words, who controls the world?
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6:34 - 6:37I think this is an interesting question.
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6:37 - 6:41And it has implications for systemic risk.
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6:41 - 6:46This is a measure of how vulnerable a system is overall.
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6:46 - 6:49A high degree of interconnectivity
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6:49 - 6:51can be bad for stability,
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6:51 - 6:55because then the stress can spread through the system
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6:55 - 6:58like an epidemic.
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6:58 - 7:01Scientists have sometimes criticized economists
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7:01 - 7:03who believe ideas and concepts
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7:03 - 7:06are more important than empirical data,
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7:06 - 7:09because a foundational guideline in science is:
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7:09 - 7:12Let the data speak. Okay. Let's do that.
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7:12 - 7:15So we started with a database containing
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7:15 - 7:1913 million ownership relations from 2007.
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7:19 - 7:22This is a lot of data, and because we wanted to find out
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7:22 - 7:25who rules the world,
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7:25 - 7:28we decided to focus on transnational corporations,
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7:28 - 7:30or TNCs for short.
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7:30 - 7:33These are companies that operate in more than one country,
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7:33 - 7:36and we found 43,000.
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7:36 - 7:40In the next step, we built the network around these companies,
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7:40 - 7:42so we took all the TNCs' shareholders,
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7:42 - 7:44and the shareholders' shareholders, etc.,
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7:44 - 7:47all the way upstream, and we did the same downstream,
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7:47 - 7:51and ended up with a network containing 600,000 nodes
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7:51 - 7:53and one million links.
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7:53 - 7:57This is the TNC network which we analyzed.
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7:57 - 7:59And it turns out to be structured as follows.
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7:59 - 8:02So you have a periphery and a center
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8:02 - 8:06which contains about 75 percent of all the players,
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8:06 - 8:10and in the center there's this tiny but dominant core
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8:10 - 8:15which is made up of highly interconnected companies.
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8:15 - 8:17To give you a better picture,
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8:17 - 8:19think about a metropolitan area.
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8:19 - 8:21So you have the suburbs and the periphery,
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8:21 - 8:24you have a center like a financial district,
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8:24 - 8:26then the core will be something like
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8:26 - 8:29the tallest high rise building in the center.
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8:29 - 8:34And we already see signs of organization going on here.
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8:34 - 8:40Thirty-six percent of the TNCs are in the core only,
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8:40 - 8:44but they make up 95 percent of the total operating revenue
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8:44 - 8:47of all TNCs.
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8:47 - 8:49Okay, so now we analyzed the structure,
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8:49 - 8:53so how does this relate to the control?
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8:53 - 8:57Well, ownership gives voting rights to shareholders.
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8:57 - 9:00This is the normal notion of control.
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9:00 - 9:03And there are different models which allow you to compute
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9:03 - 9:06the control you get from ownership.
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9:06 - 9:08If you have more than 50 percent of the shares in a company,
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9:08 - 9:10you get control,
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9:10 - 9:15but usually it depends on the relative distribution of shares.
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9:15 - 9:18And the network really matters.
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9:18 - 9:21About 10 years ago, Mr. Tronchetti Provera
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9:21 - 9:24had ownership and control in a small company,
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9:24 - 9:28which had ownership and control in a bigger company.
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9:28 - 9:29You get the idea.
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9:29 - 9:32This ended up giving him control in Telecom Italia
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9:32 - 9:36with a leverage of 26.
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9:36 - 9:40So this means that, with each euro he invested,
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9:40 - 9:44he was able to move 26 euros of market value
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9:44 - 9:47through the chain of ownership relations.
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9:47 - 9:50Now what we actually computed in our study
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9:50 - 9:54was the control over the TNCs' value.
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9:54 - 9:57This allowed us to assign a degree of influence
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9:57 - 9:59to each shareholder.
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9:59 - 10:01This is very much in the sense of
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10:01 - 10:05Max Weber's idea of potential power,
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10:05 - 10:08which is the probability of imposing one's own will
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10:08 - 10:12despite the opposition of others.
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10:12 - 10:17If you want to compute the flow in an ownership network,
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10:17 - 10:18this is what you have to do.
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10:18 - 10:21It's actually not that hard to understand.
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10:21 - 10:24Let me explain by giving you this analogy.
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10:24 - 10:26So think about water flowing in pipes
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10:26 - 10:30where the pipes have different thickness.
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10:30 - 10:34So similarly, the control is flowing in the ownership networks
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10:34 - 10:39and is accumulating at the nodes.
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10:39 - 10:43So what did we find after computing all this network control?
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10:43 - 10:48Well, it turns out that the 737 top shareholders
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10:48 - 10:51have the potential to collectively control
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10:51 - 10:5580 percent of the TNCs' value.
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10:55 - 10:58Now remember, we started out with 600,000 nodes,
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10:58 - 11:02so these 737 top players
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11:02 - 11:06make up a bit more than 0.1 percent.
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11:06 - 11:11They're mostly financial institutions in the U.S. and the U.K.
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11:11 - 11:14And it gets even more extreme.
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11:14 - 11:18There are 146 top players in the core,
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11:18 - 11:22and they together have the potential to collectively control
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11:22 - 11:2740 percent of the TNCs' value.
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11:27 - 11:30What should you take home from all of this?
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11:30 - 11:34Well, the high degree of control you saw
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11:34 - 11:39is very extreme by any standard.
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11:39 - 11:41The high degree of interconnectivity
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11:41 - 11:44of the top players in the core
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11:44 - 11:49could pose a significant systemic risk to the global economy
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11:49 - 11:52and we could easily reproduce the TNC network
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11:52 - 11:54with a few simple rules.
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11:54 - 11:57This means that its structure is probably the result
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11:57 - 11:59of self-organization.
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11:59 - 12:02It's an emergent property which depends
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12:02 - 12:05on the rules of interaction in the system,
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12:05 - 12:08so it's probably not the result of a top-down approach
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12:08 - 12:12like a global conspiracy.
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12:12 - 12:15Our study "is an impression of the moon's surface.
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12:15 - 12:16It's not a street map."
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12:16 - 12:18So you should take the exact numbers in our study
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12:18 - 12:20with a grain of salt,
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12:20 - 12:23yet it "gave us a tantalizing glimpse
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12:23 - 12:28of a brave new world of finance."
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12:28 - 12:32We hope to have opened the door for more such research in this direction,
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12:32 - 12:37so the remaining unknown terrain will be charted in the future.
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12:37 - 12:38And this is slowly starting.
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12:38 - 12:41We're seeing the emergence of long-term
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12:41 - 12:45and highly-funded programs which aim at understanding
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12:45 - 12:50our networked world from a complexity point of view.
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12:50 - 12:52But this journey has only just begun,
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12:52 - 12:57so we will have to wait before we see the first results.
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12:57 - 13:01Now there is still a big problem, in my opinion.
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13:01 - 13:06Ideas relating to finance, economics, politics,
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13:06 - 13:09society, are very often tainted
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13:09 - 13:13by people's personal ideologies.
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13:13 - 13:17I really hope that this complexity perspective
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13:17 - 13:22allows for some common ground to be found.
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13:22 - 13:25It would be really great if it has the power
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13:25 - 13:30to help end the gridlock created by conflicting ideas,
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13:30 - 13:35which appears to be paralyzing our globalized world.
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13:35 - 13:40Reality is so complex, we need to move away from dogma.
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13:40 - 13:43But this is just my own personal ideology.
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13:43 - 13:45Thank you.
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13:45 - 13:50(Applause)
- Title:
- Who controls the world?
- Speaker:
- James B. Glattfelder
- Description:
-
James Glattfelder studies complexity: how an interconnected system -- say, a swarm of birds -- is more than the sum of its parts. And complexity theory, it turns out, can reveal a lot about how the economy works. Glattfelder shares a groundbreaking study of how control flows through the global economy, and how concentration of power in the hands of a shockingly small number leaves us all vulnerable. (Filmed at TEDxZurich.)
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDTalks
- Duration:
- 14:10
Krystian Aparta commented on English subtitles for Who controls the world? | ||
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Krystian Aparta edited English subtitles for Who controls the world? | ||
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Morton Bast edited English subtitles for Who controls the world? |
Krystian Aparta
The English transcript was updated on 12/12/2016.