More Trouble for Greece?

For a more dynamic view of such analyses you may wish to explore our, recently developed, tool MapView. It is free to download as is the operating Manual (but it isn’t really so complicated as that may suggest).

If you decide to do this please drop me an email and I shall forward a zip file containing reports for US and European countries:

Here are some Complexity Facts based upon our work.

The complexity of the Greece’s economic system is in free fall. In the previous Ontonix blog on the evolution of the complexity of the structure of European Union’s economy we have seen that it was possible to predict, in advance, the effects of the sub-prime crisis and that the economic recovery is much stronger for the founding member countries (EU 15) than that of the countries that have joined after May 1, 2004 (EU12).

Read more of this post

Scientists Seek Warning Signs for Catastrophic Tipping Points

In case anyone is reading my blog for the first time – shame on you – or you have read bits and pieces without ever really thinking too much about complexity or systems, THIS may be the article that changes all that! Because, what the scientists have been trying to figure out, is what Ontonix are able to achieve by measuring system complexity:

Tipping points are found in ecosystems, economies and even bodies. But they’re usually recognized in retrospect, when it’s too late for anything but regret.

Now a growing body of research suggests there are telltale mathematical signals. If scientists can figure out how to detect them, they may be able to forecast tipping points ahead of time.

“We are repeatedly blindsided by disasters that come out of the blue. If we had better tools for anticipating those events, we could avoid some of them,” said Steve Carpenter, a University of Washington ecologist and co-author of a review Wednesday in Nature.

In 1982, physicist Kenneth Wilson won a Nobel Prize for developing equations to describe transitions that don’t happen in a linear, easily predictable way, but are sudden and massive, such as fluids becoming turbulent and metals becoming magnetized.

Since then, scientists have noticed similar shifts elsewhere. The theory provides the only models that make sense of the Sahara’s sudden flip from fertile grassland to sandy wastes some 5,500 years ago. Exploited fish populations fluctuate wildly. Futures prices on the S&P 500 displayed telltale skewing in the year preceding the 1987 stock market crash.

The proposition is by no means certain, but the possibility of being able to predict these sorts of events is tantalizing.

via Scientists Seek Warning Signs for Catastrophic Tipping Points | Wired Science |

Still don’t “get” Complexity? Try this…

This brief extract is from an excellent paper “Tipping Point”  by Dr David Korowicz of FEASTA who tells me that, it was, “an attempt to describe globalised complexity in more popular form”. In my opinion it is considerably more than that!

I have tried this myself and it isn’t easy but I think he has done a great job. Judge for yourself.

Last year I used one of his video presentations with the (not at all) understated title of:

All you could ever want to know about why complexity is THE big deal if you want to gain an understanding you won’t be disappointed.

Here is a vivid description of one aspect of complexity by Eric Beinhocker who compares the number of distinct culturally produced artefacts produced by the Yanomamo tribe on the Orinoco River, and modern New Yorkers. The Yanomamo have a few hundred, the New Yorkers have in the order of tens of billions, and this wealth is a measure of complexity:

”To summarize 2.5 million years of economic history in brief: for a very, very long time not much happened; then all of a sudden all hell broke loose. It took 99.4% of economic history to reach the wealth levels of the Yanomamo, 0.59% to double that level by 1750, and then just 0.01% for global wealth to reach the level of the modern world”

Or we can look at it from the point of view of the supply-chains that are required to transform raw materials into products and services that criss-cross the globe. It is said that a modern car manufacturer has about 15,000 inputs to the manufacturing process. If each of those components was made by a supplier who put  together on average 1500 components (10%), and each of those was put together by a supplier who put together 150 components, that makes over 3 billion interactions- and we have not included staff, plant, production lines, IT and financial systems. Nor are we at the end of the story here.

For the car manufacturer would not exist were there not customers who could afford to buy a new car, which depends upon their economic outputs which are themselves dependent upon vast complex supply chains, and so on. Nor could these vast networks of exchange exist without transport, finance, and communications networks. And those networks would not be economically viable unless they were benefiting from the economies of scale shared with many other products and services. In this way we can start to see how intimately connected we are with one another across the planet, and why we see the global economy as a singular system