A different sort of financial power transfer happens today. A new power transfer that isn’t purely economic and it’s not financial either. Although it commands power, brings freedom, surpasses economics and trumps finance — it really doesn’t involve digital bits traveling at the speed of light and it doesn’t count on interbank rates involved, nor does it involve Quantitative Easing infusions of capital from the Treasurer of the US or from the Chancellor in the UK and from the Federal Reserve or the Bank of England and the exchequer.
You know this transfer of power happens instantaneously, because the people have woken up to the grim reality of the dictatorial oligarchy managing the global wealth in a very undemocratic fashion. And it just so happens because of the occupy Wall Street movement and because of the St Paul’s occupy the City movement protests and their like who sweep our world and occupy the media sphere. These movements typically in New York and London spread to the periphery like a benevolent type of contagion and shake up the orthodoxy. The also cause a major psychological upheaval aimed at the established traditions of the financial status quo. We are experiencing in the West, the same progress as any evolutionary process or even a revolutionary convulsion in the western world mimicking the Arab spring, might represent.
And it is at long last that 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, but it is certainly news to us and the mainstream public. Because of this study that proves this we are wiser and far more able to control impacts and mitigate the unseen power effects. Transparency brings accountability and proper management with it. And this monumental undertaking of a study, performed by a trio of complex systems theorists at the Swiss Federal Institute of Technology in Zürich, is the first of it’s kind. Because it is the very first study to go beyond ideology in order to empirically identify this network of power and it’s effects. and it combines 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 lead systems theorist, 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 Zürich financial research team now can conclusively demonstrate this. 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 shareholdings 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. 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 control the global economy, but rather to offer beneficial insights into economic stability and the effects of oligopoly.
Concentration of power is not good or bad in itself, says the Zürich 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 whole 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 Zürich 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.SHORT-TERM thinking is a criticism often levelled at corporations and banks by anti-capitalist protesters, and they may well be right. A lack of concern for the future is built mathematically into economic theory, and this carries through to the behaviour of companies and governments. But a different way of putting a financial value on the future is changing that.
Economists assume that society will gradually get richer, typically by about 3 per cent a year – occasional crashes notwithstanding. To account for this, they “discount” future events: models might value a resource at $100 if it’s immediately available, but only $97 if it is only available in a year’s time.
The problem, says economist John Geanakopoulos of Yale University, is that models shave off the same percentage every year. As a result, the value of assets decreases exponentially, and is effectively zero within decades or centuries. So economics effectively ignores far-future events, even if they are world-shattering.
Exponential discounting’s reign is an accident of history: early 20th-century economist Paul Samuelson introduced it as a simple solution but emphasised that it wasn’t necessarily right. In fact real humans do not discount exponentially. Questionnaire studies show that the rate at which we discount resources with time decreases gradually, not exponentially: we behave as if resources do still have a value significantly greater than zero in the distant future.
This is known in the trade as hyperbolic discounting, and although individuals and some markets display it, economists dislike it on the grounds that it is “irrational”. That’s because under hyperbolic discounting, a person has a strong preference for getting something today rather than tomorrow, but only a weak preference for getting it on day 100 rather than day 101; yet when day 100 arrives, they will strongly prefer to get the resource immediately.
In an as-yet-unpublished paper co-written with J. Doyne Farmer of the Santa Fe Institute in New Mexico, Geanakoplos claims to have shown that when you don’t know how the economy is going to change, this seemingly illogical behaviour makes mathematical sense. The pair took economic models normally used by Wall Street banks to make financial decisions that affect the following few decades, and ran them over longer timescales. When they plugged in hyperbolic discount rates, they found fewer mathematical inconsistencies in the models than when they used exponential ones. This, they say, shows that hyperbolic discounting makes more mathematical sense over extended timescales.
Economists remain sceptical about hyperbolic discounting. It is inherently inconsistent, so could lead to inconsistent policies, argues Cameron Hepburn of the London School of Economics. He has shown that using hyperbolic discounting to manage a fishery could well lead to its collapse (Environmental and Resource Economics, DOI: 10.1007/s10640-010-9354-9).
But a consensus is growing that discount rates do need to fall fast and far. And fall they will, the further you project into the future — albeit not hyperbolically. Since 2003, the UK government has been using declining discount rates to assess the impacts of policies that have ramifications lasting more than 30 years. Other European countries are following suit, and Hepburn says the US administration is discussing using hyperbolic discounting as well.
There are many ways to make the discount rate fall besides hyperbolic discounting, says Hepburn. He contributed to the 2006 Stern Review on the Economics of Climate Change, which included a declining discount rate. The review concluded that it was better to spend now to avoid climate change, rather than pay for the consequences later. The report was criticised by many economists for its approach, but Hepburn says its methods are now becoming more widely accepted. The best solution may be to model the future using a range of discounting methods, then take an average, says Matthew Salois of the University of Reading, UK.
While the most useful discounting methods will be debated for years to come, the important thing is to force economists to rethink their assumptions, because if you change the intellectual climate, you’re going to change the political climate regardless of ideology or creed and belief sets.
Yours,
Pano
PS:
The top 50 of the 147 super interconnected 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
