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.”

Economics + Math = Science?

mathematical equation

The human brain is wired to recognize patterns, which it then organizes into higher level models and theories and beliefs, which in turn it uses to explain the past and present, and to predict the future. Models offer the consolation of rationality and understanding, which provide a sense of control. All of this is foundational to classical economic theory, which assumes we approach commerce equipped with an internal rational scale that weighs supply and demand, cost and benefit, and that we then act according to our assessment of what we give for what we get back. This assumption of an internal calculus has caused mathematical modeling to reign supreme in the practice of economics.

The trouble is, humans aren’t as innately calculating as classical economics would like to believe — so says David Graeber, professor of anthropology at the London School of Economics, in his new book Bullshit Jobs: :

“According to classical economic theory, homo oeconomicus, or “economic man” — that is, the model human being that lies behind every predication made by the discipline — is assumed to be motivated by a calculus of costs and benefits.

“All the mathematical equations by which economists bedazzle their clients, or the public, are founded on one simple assumption:  that everyone, left to his own devices, will choose the course of action that provides the most of what he wants for the least expenditure of resources and effort.

 “It is the simplicity of the formula that makes the equations possible: if one were to admit that humans have complicated emotions, there would be too many factors to take into account, it would be impossible to weigh them, and predictions would not be made.

“Therefore, while an economist will say that while of course everyone is aware that human beings are not really selfish, calculating machine, assuming they are makes it possible to explain

“This is a reasonable statement as far as it goes. The problem is there are many dimensions of human life where the assumption clearly doesn’t hold. — and some of them are precisely in the domain of what we like to call the economy.”

Economics’ reliance on mathematics has been a topic of lively debate for a long time:

“The trouble… is that measurement and mathematics do not guarantee the status of science – they guarantee only the semblance of science. When the presumptions or conclusions of a scientific theory are absurd or simply false, the theory ought to be questioned and, eventually, rejected. The discipline of economics, however, is presently so blinkered by the talismanic authority of mathematics that theories go overvalued and unchecked.

“In 1886, an article in Science accused economics of misusing the language of the physical sciences to conceal ‘emptiness behind a breastwork of mathematical formulas’. More recently, Deirdre N McCloskey’s The Rhetoric of Economics(1998) and Robert H Nelson’s Economics as Religion (2001) both argued that mathematics in economic theory serves, in McCloskey’s words, primarily to deliver the message ‘Look at how very scientific I am.’

“After the Great Recession, the failure of economic science to protect our economy was once again impossible to ignore. In 2009, the Nobel Laureate Paul Krugman tried to explain it in The New York Times with a version of the mathiness diagnosis. ‘As I see it,’ he wrote, ‘the economics profession went astray because economists, as a group, mistook beauty, clad in impressive-looking mathematics, for truth.’ Krugman named economists’ ‘desire… to show off their mathematical prowess’ as the ‘central cause of the profession’s failure’.

“The result is people… who trust the mathematical exactitude of theories without considering their performance – that is, who confuse math with science, rationality with reality.

“There is no longer any excuse for making the same mistake with economic theory. For more than a century, the public has been warned, and the way forward is clear. It’s time to stop wasting our money and recognise the high priests for what they really are: gifted social scientists who excel at producing mathematical explanations of economies, but who fail, like astrologers before them, at prophecy.”

The New Astrology:  By fetishising mathematical models, economists turned economics into a highly paid pseudoscience,” Aeon Magazine

Economists may bristle at being compared to astrologers, but as we have seen, their skill at prediction seems about comparable.

In the coming weeks we’ll look at other models emerging from the digital revolution, consider what they can tell us that classical economic theory can’t, and how they are affecting the world of work.

Capitalism on the Fritz

“In November 2008, as the global financial crash was gathering pace, the 82-year-old British monarch Queen Elizabeth visited the London School of Economics. She was there to open a new building, but she was more interested in the assembled academics. She asked them an innocent but pointed question. Given its extraordinary scale, how as it possible that no one saw it coming?

“The Queen’s question went to the heart of two huge failures. Western capitalism came close to collapsing in 2007-2008 and has still not recovered. And the vast majority of economists had not understood what was happening.”

rethinking capitalismThat’s from the Introduction to Rethinking Capitalism (2016), edited by Michael Jacobs and Mariana Mazzucato.[1] The editors and authors review a catalogue of chronic economic “dysfunction” that they trace to policy-makers’ continued allegiance to neoliberal economic orthodoxy even as it has been breaking down over the past four decades.

Before we get to their dysfunction list, let’s give the other side equal time. First, consider an open letter from Warren Buffett published in Time last week. It begins this way:

“I have good news. First, most American children are going to live far better than their parents did. Second, large gains in the living standards of Americans will continue for many generations to come.”

Mr. Buffett acknowledges that “The market system… has also left many people hopelessly behind,” but assures us that “These devastating side effects can be ameliorated,” observing that “a rich family takes care of all its children, not just those with talents valued by the marketplace.” With this compassionate caveat, he is definitely bullish on America’s economy:

“In the years of growth that certainly lie ahead, I have no doubt that America can both deliver riches to many and a decent life to all. We must not settle for less.”

So, apparently, is our Congress. The new tax law is a virtual pledge of allegiance to the neoliberal economic model. Barring a significant pullback of the law (which seems unlikely), we now have eight years to watch how its assumptions play out.

And now, back to Rethinking Capitalism’s dysfunction’s list (which I’ve seen restated over and over in my research):

  • Production and wages no longer move in tandem — the latter lag behind the former.
  • This has been going on now for several decades,[2] during which living standards (adjusted) for the majority of households have been flat.
  • This is a problem because consumer spending accounts for over 70% of U.S. GDP. What hurts consumers hurts the whole economy.
  • What economic growth there has been is mostly the result of spending fueled by consumer and corporate debt. This is especially true of the post-Great Recession “recovery.”
  • Meanwhile, companies have been increasing production through increased automation — most recently through intelligent machines — which means getting more done with fewer employees.
  • That means the portion of marginal output attributable to human (wage-earner) effort is less, which causes consumer incomes to fall.
  • The job marketplace has responded with new dynamics, featuring a worldwide rise of “non-standard’ work (temporary, part-time, and self-employed).[3]
  • Overall, there has been an increase in the number of lower-paid workers and a rise in intransigent unemployment — especially among young people.
  • Adjusting to these new realities has left traditional wage-earners with feelings of meaninglessness and disempowerment, fueling populist backlash political movements.
  • In the meantime, economic inequality (both wealth and income) has grown to levels not seen since pre-revolution France, the days of the Robber Barons, and the Roaring 20’s.
  • Economic inequality means that the shrinking share of compensation paid out in wages, salaries, bonuses, and benefits has been dramatically skewed toward the top of the earnings scale, with much less (both proportionately and absolutely) going to those at the middle and bottom. [4]
  • Increased wealth doesn’t mean increased consumer spending by the top 20% sufficient to offset lost demand (spending) by the lower 80% of income earners, other than as reflected by consumer debt.
  • Instead, increased wealth at the top end is turned into “rentable” assets — e.g., real estate. intellectual property, and privatized holdings in what used to be the “commons” — which both drives up their value (cost) and the rent derived from them. This creates a “rentier” culture in which lower income earners are increasingly stressed to meet rental rates, and ultimately are driven out of certain markets.
  • Inequality has also created a new working class system, in which a large share of workers are in precarious/uncertain/unsustainable employment and earning circumstances.
  • Inequality has also resulted in limitations on economic opportunity and social mobility — e.g., there is a new kind of “glass floor/glass ceiling” below which the top 20% are unlikely to fall and the bottom 80% are unlikely to rise.
  • In the meantime, the social safety nets that developed during the post-WWII boom (as Buffett’s “rich family” took care of “all its children”) have been largely torn down since the advent of “workfare” in the 80’s and 90’s, leaving those at the bottom and middle more exposed than ever.

The editors of Rethinking Capitalism believe that “These failings are not temporary, they are structural.” That conclusion has led some to believe that people like Warren Buffett are seriously misguided in their continued faith in Western capitalism as a reliable societal institution.

More on that next time.

[1] Michael Jacobs is an environmental economist and political theorist; at the time the book was published, he was a visiting professor at University College of London. Mariana Mazzucato is an economics professor at the University of Sussex.

[2] “In the US, real median household income was barely higher in 2014 than it had been in 1990, though GDP had increased by 78 percent over the same period. Though beginning earlier in the US, this divergence of average incomes from overall economic growth has not become a feature of most advanced economies.”  Rethinking Capitalism

[3] These have accounted for “half the jobs created since the 1990s and 60 per cent since the 2008 crisis.” Rethinking Capitalism

[4] Meanwhile, those at the very top of the income distribution have done exceedingly well… In the US, the incomes of the richest 1 percent rose by 142 per cent between 1980 and 2013 (from an average of $461,910, adjusted for inflation, to $1,119,315) and their share of national income doubled, from 10 to 20 per cent. In the first three years of the recovery after the 2008 crash, an extraordinary 91 per cent of the gains in income went to the richest one-hundredth of the population.” Rethinking Capitalism