Complexity and Geomagnetic Storms

A Perfect Storm of Planetary Proportions is a fascinating article linking two of my pet fascinations: complexity and catastrophe.The immediate prompt for the article is the expected 2012-13 peaking in solar activity and the potential it has for a geomagnetic superstorm that could disrupt power grids all over the world. The article provides lots of fascinating detail about the storms themselves. Here I focus on the connection to the disruption of power grids

From where we sit, the sun seems quiet enough. And yet it is constantly bombarding Earth with electrons, protons, and radio through X-ray waves. ... Under normal circumstances, this solar wind produces only negligible effects on Earth. Occasionally, though, the sun erupts violently, emitting solar flares or throwing out coronal mass ejections consisting of billions of tons of charged particles. ...

But how does all this space weather cause damage down on the ground? It's a multistep process. First, the intense magnetic field variations in the magnetosphere induce electric fields and currents over large areas of Earth's surface. In turn, this geoelectric field creates what are known as geomagnetically induced currents, or GICs, which flow in any available conductor, including high-voltage transmission lines, oil and gas pipelines, railways, and undersea communications cables. These interconnecting networks essentially act as giant antennas that channel the induced currents from the ground. Hit with a 300-ampere GIC, a high-voltage transformer's paper tape insulation will burn, its copper winding will melt, and the transformer will fail, either right then and there or in the future. High-voltage power grids are designed to withstand the loss of any single important element, such as a substation transformer, and then recover within a half hour or so. For a terrestrial storm like a hurricane or a tornado, this approach works well. But a severe geomagnetic storm covering an entire continent would cause multiple failures all at once.

The video below discusses the most recent major geomagnetic storm from 1989, a storm of roughly 1/10 the magnitude of those known to have occurred in the past. The last time we had a truly powerful storm was in 1921—decades before developed economies became utterly dependent on electrical infrastructure. So here we have a wonderful example of how complexity begets more complexity -- how the development of a complex technological infrastructure has led to the emergence of a new type of problem; a problem that requires yet more complexity (in the software and other aspects that manage the grid) in order to minimize the potential for widespread blackouts.

The limits of mechanistic understanding

Trials and Errors: Why Science Is Failing Us uses the story of a failed drug, torcetrapib, to illustrate issues involved with understanding complex systems. It begins with a critique of mechanistic reductionism.

The story of torcetrapib is a tale of mistaken causation. Pfizer was operating on the assumption that raising levels of HDL cholesterol and lowering LDL would lead to a predictable outcome: Improved cardiovascular health. Less arterial plaque. Cleaner pipes. But that didn’t happen.
....
Pfizer invested more than $1 billion in the development of the drug and $90 million to expand the factory that would manufacture the compound. Because scientists understood the individual steps of the cholesterol pathway at such a precise level, they assumed they also understood how it worked as a whole.

This assumption—that understanding a system’s constituent parts means we also understand the causes within the system—is not limited to the pharmaceutical industry or even to biology. It defines modern science. In general, we believe that the so-called problem of causation can be cured by more information, by our ceaseless accumulation of facts. Scientists refer to this process as reductionism. By breaking down a process, we can see how everything fits together; the complex mystery is distilled into a list of ingredients.

After a discussion of the problems involved in establishing causation, the article argues that science of the past few decades has pragmatically sidestepped these problems through the use of statistics and the substitution of establishing correlation for establishing causality.

But here’s the bad news: The reliance on correlations has entered an age of diminishing returns. At least two major factors contribute to this trend. First, all of the easy causes have been found, which means that scientists are now forced to search for ever-subtler correlations, mining that mountain of facts for the tiniest of associations. Is that a new cause? Or just a statistical mistake? The line is getting finer; science is getting harder. Second—and this is the biggy—searching for correlations is a terrible way of dealing with the primary subject of much modern research: those complex networks at the center of life. While correlations help us track the relationship between independent measurements, such as the link between smoking and cancer, they are much less effective at making sense of systems in which the variables cannot be isolated. Such situations require that we understand every interaction before we can reliably understand any of them. Given the byzantine nature of biology, this can often be a daunting hurdle, requiring that researchers map not only the complete cholesterol pathway but also the ways in which it is plugged into other pathways. (The neglect of these secondary and even tertiary interactions begins to explain the failure of torcetrapib, which had unintended effects on blood pressure. It also helps explain the success of Lipitor, which seems to have a secondary effect of reducing inflammation.) Unfortunately, we often shrug off this dizzying intricacy, searching instead for the simplest of correlations. It’s the cognitive equivalent of bringing a knife to a gunfight.

The piece ends with a paragraph that links back to an earlier discussion of the role of perception in establishing causation and hints at the importance of distinguishing between the known and the unknown.

And yet, we must never forget that our causal beliefs are defined by their limitations. For too long, we’ve pretended that the old problem of causality can be cured by our shiny new knowledge. If only we devote more resources to research or dissect the system at a more fundamental level or search for ever more subtle correlations, we can discover how it all works. But a cause is not a fact, and it never will be; the things we can see will always be bracketed by what we cannot. And this is why, even when we know everything about everything, we’ll still be telling stories about why it happened. It’s mystery all the way down.

Human agency and the Euro crisis

Social systems, unlike natural systems, involve human agents who act with particular intentions. The current Euro drama illustrates this nicely. Paul Mason's 'tankist view of the Euro crisis' uses a brilliant physical analogy to clearly explain the deal that was struck a week ago:

In search of a metaphor in this crisis, I repeatedly come back to tank armour. An ultra-modern tank is almost impossible to kill because it is covered with a mixture of ceramic, textile and metal plating that is designed to disperse the incoming energy of an anti-tank projectile: laterally.

After it's done its job the armour does not look pretty, but it works - as long as you don't get hit again.

For all the criticism of the eurozone - the greyness of the political elite, the indecision, the bunga bunga etc - their strategy is not just "kicking the can down the road". It is about dispersing the energy of the debt explosion. For velocity itself is important in the kind of collision we are talking about: over-accumulated debt impacting on real world growth. If you can slow it down, a debt explosion looks like just a long, dreary recession as people pay down their borrowings.

Now to the design of the armour: the complex system being - I will not say designed, but improvised - is composed of layers.

Layer one is the Greek debt write-off. This disperses the stress away from the Greek treasury - which can no longer control its ballooning deficits - and into the EU banking system. ....

The second layer of armour is the 108bn euro bank recapitalisation programme: money from states, Far Eastern investors and the EFSF bailout fund (see below) will be used to shore up the balance sheets of the affected banks. To visualise this, again, imagine a uranium dart hitting a surface that spreads the impact - in this case across a complex fabric of financial entities stretching from Dubai to Shanghai. ...

The deepest layer of armour Europe is trying to clad itself with is the EFSF. There is 726bn euros of taxpayers money committed, which translates into 440bn euros lendable. What they are trying to do is turn that into 1.4tn euros lendable - and the Brits want even larger - by getting, again, global lenders - including China, Brazil, the IMF and Middle East Money - to lend against the 440bn: once again spreading the impact laterally. ...

At each level then, the EU response consists in taking a concentrated impact and spreading it out - across Europe, across the world, and over time.

Given that the post was written a couple days before Greece's decision to hold a referendum on the European Union aid package intended to resolve the country's debt crisis (a decision that has now been withdrawn), Mason was prescient in his observation on the limits of his physical analogy.

However, in economics as opposed to inert matter, there is the problem of people not wanting to take the hit. Right now nobody wants to admit they are even putting themselves in line to take the hit: the German parliament, the kebab-shop phobic Italian right, the IMF, the Greek people. Everybody wants someone else to take the hit.

Network Analysis of A Complex Global System: the 147 Super-Connected Corporations that Run the World

Revealed – the capitalist network that runs the world
By wmw_admin on October 21, 2011

Andy Coghlan and Debbie MacKenzie – New Scientist October 19, 2011


[Caption: The 1318 transnational corporations that form the core of the economy. Superconnected companies are red, very connected companies are yellow. The size of the dot represents revenue.]

AS PROTESTS against financial power sweep the world this week, science may have confirmed the protesters’ worst fears. An analysis of the relationships between 43,000 transnational corporations has identified a relatively small group of companies, mainly banks, with disproportionate power over the global economy.

The study’s assumptions have attracted some criticism, but complex systems analysts contacted by New Scientist say it is a unique effort to untangle control in the global economy. Pushing the analysis further, they say, could help to identify ways of making global capitalism more stable.

The idea that a few bankers control a large chunk of the global economy might not seem like news to New York’s Occupy Wall Street movement and protesters elsewhere (see photo). But the study, by a trio of complex systems theorists at the Swiss Federal Institute of Technology in Zurich, is the first to go beyond ideology to empirically identify such a network of power. It combines the mathematics long used to model natural systems with comprehensive corporate data to map ownership among the world’s transnational corporations (TNCs).

“Reality is so complex, we must move away from dogma, whether it’s conspiracy theories or free-market,” says James Glattfelder. “Our analysis is reality-based.”

Previous studies have found that a few TNCs own large chunks of the world’s economy, but they included only a limited number of companies and omitted indirect ownerships, so could not say how this affected the global economy – whether it made it more or less stable, for instance.

The Zurich team can. From Orbis 2007, a database listing 37 million companies and investors worldwide, they pulled out all 43,060 TNCs and the share ownerships linking them. Then they constructed a model of which companies controlled others through shareholding networks, coupled with each company’s operating revenues, to map the structure of economic power.

The work, to be published in PloS One, revealed a core of 1318 companies with interlocking ownerships (see image). Each of the 1318 had ties to two or more other companies, and on average they were connected to 20. What’s more, although they represented 20 per cent of global operating revenues, the 1318 appeared to collectively own through their shares the majority of the world’s large blue chip and manufacturing firms – the “real” economy – representing a further 60 per cent of global revenues.

When the team further untangled the web of ownership, it found much of it tracked back to a “super-entity” of 147 even more tightly knit companies – all of their ownership was held by other members of the super-entity – that controlled 40 per cent of the total wealth in the network. “In effect, less than 1 per cent of the companies were able to control 40 per cent of the entire network,” says Glattfelder. Most were financial institutions. The top 20 included Barclays Bank, JPMorgan Chase & Co, and The Goldman Sachs Group.

John Driffill of the University of London, a macroeconomics expert, says the value of the analysis is not just to see if a small number of people controls the global economy, but rather its insights into economic stability.

Concentration of power is not good or bad in itself, says the Zurich team, but the core’s tight interconnections could be. As the world learned in 2008, such networks are unstable. “If one [company] suffers distress,” says Glattfelder, “this propagates.”

“It’s disconcerting to see how connected things really are,” agrees George Sugihara of the Scripps Institution of Oceanography in La Jolla, California, a complex systems expert who has advised Deutsche Bank.

Yaneer Bar-Yam, head of the New England Complex Systems Institute (NECSI), warns that the analysis assumes ownership equates to control, which is not always true. Most company shares are held by fund managers who may or may not control what the companies they part-own actually do. The impact of this on the system’s behaviour, he says, requires more analysis.

Crucially, by identifying the architecture of global economic power, the analysis could help make it more stable. By finding the vulnerable aspects of the system, economists can suggest measures to prevent future collapses spreading through the entire economy. Glattfelder says we may need global anti-trust rules, which now exist only at national level, to limit over-connection among TNCs. Bar-Yam says the analysis suggests one possible solution: firms should be taxed for excess interconnectivity to discourage this risk.

One thing won’t chime with some of the protesters’ claims: the super-entity is unlikely to be the intentional result of a conspiracy to rule the world. “Such structures are common in nature,” says Sugihara.

Newcomers to any network connect preferentially to highly connected members. TNCs buy shares in each other for business reasons, not for world domination. If connectedness clusters, so does wealth, says Dan Braha of NECSI: in similar models, money flows towards the most highly connected members. The Zurich study, says Sugihara, “is strong evidence that simple rules governing TNCs give rise spontaneously to highly connected groups”. Or as Braha puts it: “The Occupy Wall Street claim that 1 per cent of people have most of the wealth reflects a logical phase of the self-organising economy.”

So, the super-entity may not result from conspiracy. The real question, says the Zurich team, is whether it can exert concerted political power. Driffill feels 147 is too many to sustain collusion. Braha suspects they will compete in the market but act together on common interests. Resisting changes to the network structure may be one such common interest.

The top 50 of the 147 superconnected companies

1. Barclays plc
2. Capital Group Companies Inc
3. FMR Corporation
4. AXA
5. State Street Corporation
6. JP Morgan Chase & Co
7. Legal & General Group plc
8. Vanguard Group Inc
9. UBS AG
10. Merrill Lynch & Co Inc
11. Wellington Management Co LLP
12. Deutsche Bank AG
13. Franklin Resources Inc
14. Credit Suisse Group
15. Walton Enterprises LLC
16. Bank of New York Mellon Corp
17. Natixis
18. Goldman Sachs Group Inc
19. T Rowe Price Group Inc
20. Legg Mason Inc
21. Morgan Stanley
22. Mitsubishi UFJ Financial Group Inc
23. Northern Trust Corporation
24. Société Générale
25. Bank of America Corporation
26. Lloyds TSB Group plc
27. Invesco plc
28. Allianz SE 29. TIAA
30. Old Mutual Public Limited Company
31. Aviva plc
32. Schroders plc
33. Dodge & Cox
34. Lehman Brothers Holdings Inc*
35. Sun Life Financial Inc
36. Standard Life plc
37. CNCE
38. Nomura Holdings Inc
39. The Depository Trust Company
40. Massachusetts Mutual Life Insurance
41. ING Groep NV
42. Brandes Investment Partners LP
43. Unicredito Italiano SPA
44. Deposit Insurance Corporation of Japan
45. Vereniging Aegon
46. BNP Paribas
47. Affiliated Managers Group Inc
48. Resona Holdings Inc
49. Capital Group International Inc
50. China Petrochemical Group Company

* Lehman still existed in the 2007 dataset used

Source