James B. Glattfelder: Who controls the world?

Translator: Joseph Geni Reviewer: Morton Bast

翻译人员: Yuxiang Yang 校对人员: Jingxian Feng

“当危机来临时，

"When the crisis came,

现有经济和金融模型的严重局限性

the serious limitations of existing economic and financial models

就立刻变得显而易见了。”

immediately became apparent."

”我很坚信的一点，也是我想和大家分享的是：

"There is also a strong belief, which I share,

that bad or oversimplistic and overconfident economics

不好的或是极其粗旷和自负的经济发展方式

helped create the crisis."

促成了危机的来临。“

Now, you've probably all heard of similar criticism

现在，你们很可能已经听到了

来自那些对资本主义持怀疑态度的人的相似的批评。

coming from people who are skeptical of capitalism.

But this is different.

但其实这是不一样的。

这个问题产生于金融的核心。

This is coming from the heart of finance.

The first quote is from Jean-Claude Trichet

第一句引述来自于

when he was governor of the European Central Bank.

前欧洲央行行长特里谢。

The second quote is from the head of the UK Financial Services Authority.

第二句引述来自

英国金融服务局局长。

Are these people implying

他们是否想暗示

that we don't understand the economic systems

我们并不了解那些促进我们现代社会的

that drive our modern societies?

经济体系呢？

It gets worse.

这变得很糟糕。

"We spend billions of dollars

“我们花费大量的金钱

trying to understand the origins of the universe,

来试图了解宇宙的起源。

然而我们却仍然不明白

while we still don't understand the conditions for a stable society,

一个稳定的社会，良好的经济，或者和谐所需要的条件。”

a functioning economy, or peace."

What's happening here? How can this be possible?

到底发生了什么？这一切又是如何发生的？

Do we really understand more about the fabric of reality

对于由人类交互而产生的现实世界，

than we do about the fabric which emerges from our human interactions?

我们对它的理解是否真的

比对它的建设更多呢？

Unfortunately, the answer is yes.

遗憾的是，答案是肯定的。

But there's an intriguing solution

但是复杂性科学

which is coming from what is known as the science of complexity.

提供了一个有趣的解决方案。

为了说明这是什么及其所代表的含义，

To explain what this means and what this thing is,

please let me quickly take a couple of steps back.

请容许我简要回顾一下我的过去。

一个偶然的机会，我学习了物理。

I ended up in physics by accident.

It was a random encounter when I was young,

这是我小时候的一个插曲，

and since then, I've often wondered about the amazing success of physics

并且从那以后，我便经常想知道

物理学在描述我们每天所处的现实世界方面

所获得的巨大成功。

in describing the reality we wake up in every day.

简单来说，你能想到的物理是这样的：

In a nutshell, you can think of physics as follows.

So you take a chunk of reality you want to understand

你想要了解一系列的物理现象

and you translate it into mathematics.

然后你用数学对这一系列的物理现象进行建模。

你再把数学模型编译为数学方程。

You encode it into equations.

Then, predictions can be made and tested.

最后我们可以对结果作出推断和测试。

We're actually really lucky that this works,

我们的确很幸运对于这一切都能够行得通，

because no one really knows why the thoughts in our heads

因为没有人真正知道我们的思想

should actually relate to the fundamental workings of the universe.

为何与宇宙的基本规律有一定的联系。

Despite the success, physics has its limits.

尽管如此，物理学仍然有它的局限性。

As Dirk Helbing pointed out in the last quote,

就像Dirk Helbing在前一句引述中所指出的那样：

我们并不真正了解围绕在我们身边的

we don't really understand the complexity that relates to us, that surrounds us.

与我们息息相关的事物的复杂性。

This paradox is what got me interested in complex systems.

这个悖论使我对复杂系统产生了兴趣。

So these are systems which are made up

这些系统包括了很多

of many interconnected or interacting parts:

连接和交互的部分：

swarms of birds or fish,

比如说鸟群，鱼群，蚁群，

ant colonies, ecosystems, brains, financial markets.

生态系统，人的大脑，金融市场。

These are just a few examples.

这都是一些例子。

Interestingly, complex systems are very hard to map

有趣的是，复杂系统通常很难

into mathematical equations,

用数学方程来表示，

so the usual physics approach doesn't really work here.

所以通常的物理方法在这里并不适用。

So what do we know about complex systems?

那么关于复杂系统我们又知道些什么呢？

Well, it turns out that what looks like complex behavior from the outside

事实是外部看起来

复杂的行为往往

is actually the result of a few simple rules of interaction.

（复杂性）是由一些简单的交互规则所形成的。

这表明你可以忘记数学方程

This means you can forget about the equations

and just start to understand the system

而通过观察交互关系

就可以开始理解系统。

by looking at the interactions,

so you can actually forget about the equations

所以你完全可以忘记数学方程

and you just start to look at the interactions.

而仅仅从观察交互关系开始。

And it gets even better, because most complex systems

这会变得更好些，因为大部分的复杂系统

have this amazing property called emergence.

都具有一种神奇的特性——浮现。

So this means that the system as a whole suddenly starts to show a behavior

这意味着

通过观察系统的组件

能够发现系统产生的

which cannot be understood or predicted

by looking at the components of the system.

无法理解与预测的行为。

So the whole is literally more than the sum of its parts.

所以，系统整体并不是简单的局部之和。

And all of this also means

这也表明你可以忽略系统的局部

that you can forget about the individual parts of the system,

以及系统局部的复杂性。

how complex they are.

So if it's a cell or a termite or a bird,

无论组成系统的是细胞，白蚁或是小鸟，

you just focus on the rules of interaction.

你仅仅需要关注系统交互的规则即可。

因此，网络是复杂系统的

As a result, networks are ideal representations of complex systems.

理想代表。

网络中的节点

The nodes in the network are the system's components,

是系统的组件，

并且网络中的联系是通过系统间的交互来体现的。

and the links are given by the interactions.

So what equations are for physics,

数学方程适用于物理，

complex networks are for the study of complex systems.

而复杂网络则可用于复杂系统的研究。

This approach has been very successfully applied

这种方法已经成功应用于

to many complex systems in physics, biology,

许多领域的复杂系统，例如，物理学，生物学，

computer science, the social sciences,

计算机科学以及社会科学。

but what about economics?

那对于经济学究竟如何呢？

Where are economic networks?

经济体系的网络又在哪里呢？

This is a surprising and prominent gap in the literature.

在文献中，两者之间存在着巨大的差距。

我们去年发表的论文

The study we published last year, called "The Network of Global Corporate Control,"

“全球协作控制网络”

是第一个关于经济网络的广泛分析。

was the first extensive analysis of economic networks.

The study went viral on the Internet

这项研究在因特网上迅速传播开来，

and it attracted a lot of attention from the international media.

也吸引了来自国际媒体的广泛关注。

This is quite remarkable, because, again, why did no one look at this before?

这是相当引人注目的。

但为什么以前没有人做这项研究呢？

Similar data has been around for quite some time.

类似的数据已经存在了相当长的一段时间。

What we looked at in detail was ownership networks.

我们仔细研究的是所有权网络。

所有权网络中的节点是公司，公民，政府

So here the nodes are companies, people, governments, foundations, etc.

基金会等。

And the links represent the shareholding relations,

所有权网络中的联系代表了股权关系，

so shareholder A has x percent of the shares in company B.

例如，股东A占有了公司B百分之x的股份。

And we also assign a value to the company given by the operating revenue.

我们也将公司的收益

通过赋值的方式标记在每一个节点上。

因此所有权网络揭示了

So ownership networks reveal the patterns of shareholding relations.

股权关系的模型。

在这个很小的例子中，你可以看到

In this little example, you can see a few financial institutions

一些具有特别联系的

金融机构。

with some of the many links highlighted.

Now, you may think that no one looked at this before

现在，也许你会认为过去没有人研究

because ownership networks are really, really boring to study.

所有权网络是因为

它实在太无趣乏味了。

Well, as ownership is related to control,

然而，所有权与控制力是相关的，

as I shall explain later,

这个我稍后会解释，

looking at ownership networks

通过观察所有权网络你可以找到

actually can give you answers to questions like,

以下一些问题的答案，例如，

who are the key players?

谁是关键的角色？

How are they organized? Are they isolated?

他们是如何组织的？他们是孤立的吗？

Are they interconnected?

他们是相互联系的吗？

And what is the overall distribution of control?

总体的控制力分布究竟是什么？

In other words, who controls the world?

换句话说，谁主宰着世界？

I think this is an interesting question.

我认为这是一个十分有趣的问题。

这其中包含了系统危机的深层含义。

And it has implications for systemic risk.

这也是系统总体脆弱性的一个评价标准。

This is a measure of how vulnerable a system is overall.

系统高度的互联性

A high degree of interconnectivity can be bad for stability,

不利于系统的稳定，

because then the stress can spread through the system like an epidemic.

因为压力能够像流行病一样

遍布系统。

Scientists have sometimes criticized economists

科学家们有时会批判

那些认为想法和概念

who believe ideas and concepts are more important than empirical data,

比经验数据更重要的经济学家，

because a foundational guideline in science is:

这是因为科学的一条基本准则是：

用数据说话。好吧，那就这样吧。

Let the data speak. OK. Let's do that.

So we started with a database containing 13 million ownership relations from 2007.

我们从一个数据库开始，这个数据库包含了

从2007年开始的1300万条的所有权关系数据。

This is a lot of data, and because we wanted to find out

对于我们来说，数据量是极大的，

但为了能够发现谁掌控着世界,

"who rules the world,"

我们决定将注意力集中在跨国公司上，

we decided to focus on transnational corporations,

or "TNCs," for short.

跨国公司可以简单地缩写为TNCs。

These are companies that operate in more than one country,

这些公司与不止一个国家有关系，

and we found 43,000.

这样的公司有43000家。

接下来，我们组建关于跨国公司的网络，

In the next step, we built the network around these companies,

so we took all the TNCs' shareholders,

我们考虑这些跨国公司的股东

and the shareholders' shareholders, etc.,

以及股东的股东，等等。

all the way upstream, and we did the same downstream,

先自底向上，再自顶向下，

and ended up with a network containing 600,000 nodes

最终形成了一个包含60万个节点

and one million links.

和100万条联系的网络。

This is the TNC network which we analyzed.

这是我们分析的一个TNC网络。

它最终是这样组织的：

And it turns out to be structured as follows.

So you have a periphery and a center

网络由外围和中心两部分组成，

which contains about 75 percent of all the players,

其中中心包含了75%的公司，

而且，中心还存在着微小却至关重要的核心，

and in the center, there's this tiny but dominant core

这个核心是由联系高度紧密的公司所组成的。

which is made up of highly interconnected companies.

To give you a better picture,

为了能让你们更好地理解，

think about a metropolitan area.

想象一个很大的城区。

So you have the suburbs and the periphery,

这里有郊区，

you have a center, like a financial district,

也有城区的金融中心，

then the core will be something like

而TNC网络的核心就好比

the tallest high-rise building in the center.

城市金融中心的最高的那栋楼。

And we already see signs of organization going on here.

我们已经看见了呈现在眼前的组织标记。

36 percent of the TNCs are in the core only,

36%的跨国公司仅仅存在于网络的核心区域，

but they make up 95 percent of the total operating revenue of all TNCs.

但是它们却创造了

所有公司总营业收入的95%。

现在让我们来分析一下结构，

OK, so now we analyzed the structure,

so how does this relate to the control?

它是怎样与控制力联系的呢？

Well, ownership gives voting rights to shareholders.

所有权赋予股东以投票权。

This is the normal notion of control.

这是控制力的常规解释。

有不同的模式可以计算

And there are different models

which allow you to compute the control you get from ownership.

所有权的控制力。

如果你占有一个公司超过50%的股份，

If you have more than 50 percent of the shares in a company,

你就有控制力，

you get control,

but usually, it depends on the relative distribution of shares.

但是通常来说，控制力取决于占有股份的相对大小。

And the network really matters.

这个网络真的有助于我们的分析。

About 10 years ago, Mr. Tronchetti Provera

大约10年前，Provera先生

拥有一个小公司的所有权和控制力，

had ownership and control in a small company,

which had ownership and control in a bigger company.

然而这个小公司却拥有对另一个大公司的所有权和控制力。

接下来，你们可以猜到了

You get the idea.

This ended up giving him control in Telecom Italia with a leverage of 26.

这最终使他拥有了对意大利电信公司的控制力，

控制力的影响因子为26。

So this means that, with each euro he invested,

因此这表示，通过所有权关系链，

he was able to move 26 euros of market value

他每投资1欧元，就能通过所有权关系链

促使市值26欧元产生流通。

through the chain of ownership relations.

Now what we actually computed in our study was the control over the TNCs' value.

现在，在我们的研究中所计算的

是对跨国公司控制力的值。

这就允许我们对每一个股东

This allowed us to assign a degree of influence to each shareholder.

影响力的进行赋值。

这很像是从

This is very much in the sense of Max Weber's idea of potential power,

韦伯的潜力理论的角度来阐述的，

潜力表示的是一种能够无视他人的反对

which is the probability of imposing one's own will

despite the opposition of others.

而强加自己意愿的概率。

If you want to compute the flow in an ownership network,

假如你想计算所有权网络的流量，

this is what you have to do.

当然这也是你必须要做的。

It's actually not that hard to understand.

这实际上并不难理解。

Let me explain by giving you this analogy.

让我通过类比来说明，

想象一下管道中流动的水，

So think about water flowing in pipes, where the pipes have different thickness.

同时，管道的厚度是不一样的。

So similarly, the control is flowing in the ownership networks

类似地，控制力在所有权网络中流动

并在节点处累积。

and is accumulating at the nodes.

So what did we find after computing all this network control?

那么在我们计算出网络的控制力之后，我们发现了什么？

事实表明，737个顶尖的股东

Well, it turns out that the 737 top shareholders

have the potential to collectively control 80 percent of the TNCs' value.

拥有共同控制

80%公司的潜在能力。

Now remember, we started out with 600,000 nodes,

请注意，我们开始的时候有60万个节点，

so these 737 top players make up a bit more than 0.1 percent.

然而，这737个顶尖的股东

仅比所有股东的0.1%多一点点。

They're mostly financial institutions in the US and the UK.

他们大多是来自美国和英国的金融机构。

And it gets even more extreme.

更为极端的是，

有146个核心股东

There are 146 top players in the core,

他们共同拥有控制

and they together have the potential to collectively control

40 percent of the TNCs' value.

40%公司的潜在能力。

从中你能够得到什么启示呢？

What should you take home from all of this?

Well, the high degree of control you saw is very extreme by any standard.

根据任何标准，控制力的集中程度

都是极其高的。

核心股东的

The high degree of interconnectivity of the top players in the core

高度互联性

会使全球经济陷入重大的危机之中。

could pose a significant systemic risk to the global economy.

我们能够很容易地通过一些简单的规则

And we could easily reproduce the TNC network

with a few simple rules.

组建TNC网络。

这也意味着这个网络的结构是

This means that its structure is probably the result of self-organization.

系统自组织的成果。

这种新生的特性取决于

It's an emergent property which depends on the rules of interaction in the system,

系统交互的规则，

so it's probably not the result of a top-down approach

所以这并不太可能是一种自顶向下方法的结果，

like a global conspiracy.

例如国际阴谋。

我们的研究只是较为表面的东西，

Our study "is an impression of the moon's surface.

It's not a street map."

没有触及太多的细节。

So you should take the exact numbers in our study with a grain of salt,

所以，你在分析我们研究中确切的数据时应该持有保留的态度，

因为它们并不总是十分精确。

yet it "gave us a tantalizing glimpse of a brave new world of finance."

然而这的确给了我们对崭新的金融世界的

华丽的诱人一瞥。

我们希望我们已经为更多的同类研究打开了一扇门，

We hope to have opened the door for more such research in this direction,

so the remaining unknown terrain will be charted in the future.

剩下的未知都会在将来变得明朗。

And this is slowly starting.

虽然起步有点缓慢，

We're seeing the emergence of long-term and highly-funded programs

但我们能够预见将会有越来越多的

关于从复杂网络的角度来认识世界的

which aim at understanding our networked world

长期的，高额的资助项目出现。

from a complexity point of view.

然而这才刚刚开始，

But this journey has only just begun,

so we will have to wait before we see the first results.

因此在第一个成果产生以前，我们必须等待。

Now there is still a big problem, in my opinion.

如今在我看来仍然有一个大问题。

关于金融，经济，政治，

Ideas relating to finance, economics, politics, society,

社会的想法很容易受到

are very often tainted by people's personal ideologies.

人们主观意识的影响。

I really hope that this complexity perspective

我真心希望复杂性的观点

allows for some common ground to be found.

能够帮助我们发现一些共性的基础。

冲突会造成阻塞，

It would be really great if it has the power

to help end the gridlock created by conflicting ideas,

如果它能够帮助我们清除阻碍世界发展的痼疾，

which appears to be paralyzing our globalized world.

那就再好不过的了。

Reality is so complex, we need to move away from dogma.

现实世界是纷繁复杂的，我们不应该墨守成规。

But this is just my own personal ideology.

但这仅仅是我的个人理想。

Thank you.

谢谢！

(Applause)

掌声。