Who Controls the World?

murmuration

One fine afternoon autumn day in Cincinnati I watched transfixed as a gigantic flock of migratory birds swarmed over the woods across the street. I didn’t know it then, but I was watching a “complex, self-organizing system” in action. Schools of fish, ant colonies, human brains… and even the financial industry… all exhibit this behavior. And so does “the economy.”

who controls the world TED talk

James B. Glattfelder holds a Ph.D. in complex systems from the Swiss Federal Institute of Technology. He began as a physicist, became a researcher at a Swiss hedge fund. and now does quantitative research at Olsen Ltd in Zurich, a foreign exchange investment manager. He begins his TED Talk with two quotes about the Great Recession of 2007-2008:

“When the crisis came, the serious limitations of existing economic and financial models immediately became apparent.”

“There is also a strong belief, which I share, that bad or over simplistic and overconfident economics helped create the crisis.”

Then he tells us where they came from:

“You’ve probably all heard of similar criticism coming from people who are skeptical of capitalism. But this is different. This is coming from the heart of finance. The first quote is from Jean-Claude Trichet when he was governor of the European Central Bank. The second quote is from the head of the UK Financial Services Authority. Are these people implying that we don’t understand the economic systems that drive our modern societies?

That’s a rhetorical question, of course:  yes they are, and no we don’t. As a result, nobody saw the Great Recession coming, with its layoffs carnage and near-collapse of the global economy, or its “too big to fail” bailouts and generous bonuses paid to its key players.

Glattfelder tackles what that was about, from a complex systems perspective. First, he dismisses two approaches we’ve already seen discredited:

Ideologies:  “I really hope that this complexity perspective allows for some common ground to be found. It would be really great if it has the power to help end the gridlock created by conflicting ideas, which appears to be paralyzing our globalized world.  Ideas relating to finance, economics, politics, society, are very often tainted by people’s personal ideologies.  Reality is so complex, we need to move away from dogma.”

Mathematics:  “You can think of physics as follows. You take a chunk of reality you want to understand and you translate it into mathematics. You encode it into equations. Then, predictions can be made and tested. But despite the success, physics has its limits. Complex systems are very hard to map into mathematical equations, so the usual physics approach doesn’t really work here”

Then he lays out a couple key features of complex, self-organizing systems:

“It turns out that what looks like complex behavior from the outside is actually the result of a few simple rules of interaction. This means you can forget about the equations and just start to understand the system by looking at the interactions.

“And it gets even better, because most complex systems have this amazing property called emergence. This means that the system as a whole suddenly starts to show a behavior which cannot be understood or predicted by looking at the components. The whole is literally more than the sum of its parts.”

Applying this to the financial industry, he describes how his firm studied the Great Recession by analyzing a database of controlling shareholder interests in 43,000 transnational corporations (TNC’s). That analysis netted over 600,000 “nodes” of ownership, and over a million connections among them. Then came the revelation:

“It turns out that the 737 top shareholders have the potential to collectively control 80 percent of the TNCs’ value. Now remember, we started out with 600,000 nodes, so these 737 top players make up a bit more than 0.1 percent. They’re mostly financial institutions in the US and the UK. And it gets even more extreme. There are 146 top players in the core, and they together have the potential to collectively control 40 percent of the TNCs’ value.”

737 or 146 shareholders — “mostly financial institutions in the U.S. and the U.K.” — had the power to control 80% or 40% of the value of 43,000 multinational corporations. And those few hundreds — for their own accounts and through the entities they controlled — bought securitized sub-prime mortgages until the market imploded and nearly brought down the global economy valued in the tens of trillions dollars — giving a whole new meaning to the concept of financial leverage. In what might be the economic understatement of the 21st Century, Glattfelder concludes:

“This high level of concentrated ownership means these elite owners possess an enormous amount of leverage over financial risk worldwide. The high degree of control you saw is very extreme by any standard. The high degree of interconnectivity of the top players in the core could pose a significant systemic risk to the global economy.”

It took a lot of brute number-crunching computer power and some slick machine intelligence to generate all of that, but in the end there’s an innate simplicity to it all. He concludes:

[The TNC network of ownership is] “an emergent property which depends on the rules of interaction in the system. We could easily reproduce [it] with a few simple rules.”

The same is true of the mesmerizing flock of birds I watched that day:  here’s a YouTube explanation of the three simple rules that explain it[i].

[i] What I saw was a “murmuration” of birds, which is explained by a form of complex system analysis  known as “swarm behavior.”

The Perils of Policy

Economics articles, books, and speeches usually end with policy recommendations. You can predict them in advance if you know the ideological bias of the source. Let’s look at three, for comparison.

First, this Brookings Institute piece– What happens if robots take the jobs? The impact of emerging technologies on employment and public policy — written a couple years back by Darrell M. West, vice president and director of Governance Studies and founding director of the Center for Technology Innovation at the Institute.

Second, this piece — Inequality isn’t inevitable. Here’s what we can do differently — published by the World Economic Forum and written last month by a seriously over-achieving 23-year old globe-trotting Italian named Andrea Zorzetto.

Third, this piece — Mark My Words:  This Political Event Will be Unlike Anything We’ve Seen in 50 Years — by Porter Stansberry, which showed up in my Facebook feed last month. Stansberry offers this bio: “You may not know me, but nearly 20 years ago, I started a financial research and education business called Stansberry Research. Today we have offices in the U.S., Hong Kong, and Singapore. We serve more than half a million paid customers in virtually every country (172 at last count). We have nearly 500 employees, including dozens of financial analysts, corporate attorneys, accountants, technology experts, former hedge fund managers, and even a medical doctor.”

The Brookings article is what you would expect:  long, careful, reasoned. Energetic Mr. Zorzetto’s article is bright, upbeat, and generally impressive. Porter Stansberry’s missive  is … well, we’ll just let it speak for itself. I chose these three because they all cite the same economic data and developments, but reach for different policy ideals. There’s plenty more where these came from. Read enough of them, and they start to organize themselves into multiple opinion categories which after numerous iterations all mush together into vague uncertainty.

There’s got to be a better way. Turns out there is:  how about if we ask the economy itself what it’s up to? That’s what the emerging field of study called “complexity economics” does. Here’s a short explanation of it, published online by Exploring Economics, an “open source learning platform.” The word “complexity” in this context doesn’t mean “hard to figure out.” It’s a technical term borrowed from a systems theory approach that originated in science, mathematics, and statistics.

Complexity economics bypasses ideological bias and lets the raw data speak for itself. It’s amazing what you hear when you give data a voice — for example, an answer to the question we heard the Queen of England ask a few posts back, which a group of Cambridge economists couldn’t answer (neither could anyone else, for that matter):  Why didn’t we see the 2007-2008 Recession coming?  The economy had an answer; you just need to know how to listen to it. (More on that coming up.)

What gives data its voice? Ironically, the very job-threatening technological trends we’ve been talking about in the past couple months:

Big Data + Artificial Intelligence + Brute Strength Computer Processing Power
= Complexity Economics

Which means — in a stroke of delicious irony — guess whose jobs are most threatened by this new approach to economics? You guessed it:  the jobs currently held by ideologically-based economists making policy recommendations. For them, economics just became “the dismal science” in a whole new way.

Complex systems theory is as close to a Theory of Everything as I’ve seen. No kidding. We’ll be looking at it in more depth, but first… Explaining is one thing, but predicting is another. Policy-making invariably relies on the ability to predict outcomes, but predicting has its own perils, too. We’ll look at those next time.

In the meantime, just for fun…

the perils of pauline 1

 

A click on this image takes you to the original silent movie melodrama series.

 

 

the perils of pauline

 

A click on this image takes you to a Wikipedia article re: the 1947 Hollywood technicolor remake.

 

 

 

Both of these came out at significant economic times:  the first at roughly the middle of six decades of enormous economic growth and quality of life advancements; the second at the beginning of an equally powerful surge of post-WWII economic growth.

the rise and fall of american growth

Which leads to another economic history book I can’t recommend highly enough. Like Americana — the image below, which I recommended a couple weeks ago — the book is both scholarly and well researched but also highly readable. They’re both big, thick books, but together they offer a fascinating course in the American history we never knew. (Click the images for more.)

 

American larger

 

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