Today, however, Neil Johnson at the University of Florida in Miami and a few pals reveal an important insight into what’s going on. These guys have found evidence that the behaviour of financial markets changes dramatically on timescales shorter than a certain threshold level. This threshold, they say, is more or less exactly equal to the human reaction times.
The implication is clear. When humans trade and when they monitor the behaviour of machine trading, they can step in to override any unwanted behaviour. In that regime, markets behave in a specific way.
But when human oversight becomes impossible, because the trades take place faster than humans can react, a different behaviour occurs. That’s when flash crashes and rises set in.
Source: technologyreview.com
Fifty years ago, the four most valuable U.S. companies employed an average of 430,000 people with an average market cap of $180 billion. This year, the four largest U.S. companies employ an average 120,000 people with an average market cap of $334 billion. The titans of 2011 have twice the the value of their 1964 counterparts with a quarter of the employees.
(via The Atlantic)
The empheraliszation of work means that software and other machinery has replaced a great deal of human dudgery. What happens when the machines become creative?
What sort of a world if 90% of all labor becomes obsolete, and nearly no one needs to work? Society will need a dramatic rethinking if we aren’t to split into an increasingly small elite that run businesses and government, and everyone else.
Who is to benefit from massive increases in productivity?
Source: The Atlantic
The Keynesian Formula Will Not Solve Our Fundamental Growth Problem: Raghuram Rajan | Economy Watch
This is another article pointing which together with both Tyler Cowen and Joseph Stiglitz that the current economic situation is not just a financial crisis but a consequence of a deeper problem which must be fixed before. And depending on if we chose that way of looking at it or not, we will craft different futures.
The advanced countries have a choice. They can act as if all is well, except that their consumers are in a funk, and that “animal spirits” must be revived through stimulus. Or they can treat the crisis as a wake-up call to fix what debt has papered over in the last few decades. For better or worse, the narrative that persuades these countries’ governments and publics will determine their future – and that of the global economy.
Is The US In A Phase Change To The Creative Economy? - Steve Denning
Denning refers to Stieglitz’s article in Vanity Fair which states that US economy is going through a fundamental shift in the nature of the economy.
Why no recovery? The idea of the bailouts and the stimulus was that these measures would return the economy to where it had been before the crisis.
The striking part of Stiglitz’s argument is to say that this is indeed what has happened. The economy has gotten back to its former state. The problem, says Stiglitz, is that the former state of the economy was much worse than anyone realized. Getting back to where we were means getting back to a state of sickness, not to health.
Denning then argues that Stieglitz is wrong when saying that US is in process of being transformed into a service economy, when it is in fact a creative economy that lies in the future.
In the present situation I think US would benefit most from realizing that it really is a major phase transition and not just some problems in the economical machinery which can be fixed by a quick fix. The question of what kind of economy the industrialized world might be more complicated than what both Stieglitz and Denning is assuming, but I don’t believe it is the key question for any US government at this stage. If they first change mindset from maintenance mode into a transformation mode, then they can discuss the deeper issues where the economy really is heading.
This Is Europe’s Scariest Chart | ZeroHedge
the one chart that truly captures the latent fear behind the scenes in Europe is that showing youth unemployment in the continent’s troubled countries (and frankly everywhere else). Because the last thing Europe needs is a discontented, disenfranchised, and devoid of hope youth roving the streets with nothing to do, easily susceptible to extremist and xenophobic tendencies: after all, it must be “someone’s” fault that there are no job opportunities for anyone.
Source: zerohedge.com
Tattoo removal on the increase in Spain in the battle for jobs | World news | guardian.co.uk
Barcelona clinic reports 81% rise in demand for painful laser treatment to remove tattoos as competition for work intensifies
Is this signalling that a harsh economic climate will stifle individualism in the future? Or is it just about tattoos?
(via @changeist)
Source: Guardian
There are a few lessons to glean from the Surprise Index, which I was only made aware of this week. First, predictions are often reported as news. They’re not. They’re predictions, and they’re almost always wrong. Full disclosure: I’ve been as guilty as anyone for breathlessly passing along predictions without the qualifying them as conjecture. Second, to be fair to the analysts, sometimes the first draft of the economic figures aren’t any better than the predictions. A great example: We initially estimated GDP falling 3.8% in the last three months of 2008. Instead, it fell nearly 9%. That’s a horrible miscalculation that had a real impact on decisions made by Congress and the Federal Reserve to fix the economy. I wonder what the Economic Surprise Index would say about first readings of GDP and unemployment numbers.
Source: The Atlantic
Income inequality is rising in rich countries(via Incomes: Inequality street | The Economist)
THE gap between rich and poor has grown ever wider in wealthy countries over the past three decades. A new report by the OECD has reams of data on this phenomenon and is well worth looking at. The Gini coefficient, a measure of inequality in which zero corresponds to everyone having the same income and one means the richest person has all the income, increased by almost 10% from 0.29 in 1985 to 0.32 in 2008, for working-age people in OECD countries. The trend is caused by earnings: the pay of the richest 10% of employees has increased at a far greater rate than that of the poorest 10% of employees. Within the upper echelons, the top 1% have reaped the greatest gains. Technology has disproportionately benefited high-earning workers, who also spend far longer at work than do low-earners. High earners marry other high earners. And governments are doing less to redistribute wealth than they have done in the past. So far, so familiar. But the report also argues that globalisation is not a significant cause of inequality, and that one of the many reasons for the rise in income inequality is that more people are in work now (or at least they were before the financial crisis hit) compared with the 1970s.
Source: economist.com
Have you ever been thinking that there is something fundamentally wrong with the way economists view the world? One reason is that Economists apply linear and analytical models which simply don’t take into account e g non-linearity, which is exactly what we see around us today. During certain periods the world seems to behave according to linear models and things seems almost predictable, but between those stable periods non-linear or even chaotic phenomena is dominating and linearly created models becomes totally irrelevant.
This video is an interview with Doyne Farmer, a professor doing research complex systems at the Santa Fe institute. In this video he explains his project of making a bottom-up agent-based simulation of the economy.
The really interesting value with agent-based simulations is that they don’t reduce problems into a linear models. On the other hand they require calibration to reality as well as a lot of computer power to simulate the actions of millions of individuals.
What we also must know is that they are not very good at predicting future outcomes. They rather help is to learn about how certain patterns appears and how these patterns have certain emergent results. It is a tool for learning rather than predicting.
One way to understand this is to see the computer as a “macroscope” which helps us zoom in and out from individual behavior to the emergent patterns in order to understand under which circumstances e g collapses and other phenomena happens.
This emerging understanding and research of non-linearity, complexity and chaos have been interesting for scientist from many field for a couple of decades now, almost nothing of it have seems to have been applied to e g econometry. It is really urgent that this happens now and professor Doyne Farmer seems to be the right person to take the first steps towards a new complexity based theory of economics.
(via Doyne Farmer - Macroeconomics From the Bottom Up | Institute for New Economic Thinking)
Source: ineteconomics.org
