Stefan Molyneux talks about societies following the Pareto distribution which automatically leads to inequality. The Pareto distribution gives us the 80/20 rule. The Pareto distribution is also a power law distribution.
Stefan Molyneux talks about societies following the Pareto distribution which automatically leads to inequality. The Pareto distribution gives us the 80/20 rule. The Pareto distribution is also a power law distribution.
“History as seen from tail analysis,” Cirillo and Taleb conclude, “is far more risky, and conflicts far more violent than acknowledged by naive observation.”
Is the world getting more peaceful? Some academics think so. New research, though, suggests they might be getting their math wrong.
To get a clearer sense of what’s really going on, the statistician Pasquale Cirillo, working alongside Nassim Taleb of “The Black Swan” fame, did an analysis using extreme value theory — a branch of mathematics specifically designed for such problems. Looking at war data over 2,000 years, they found that violent conflicts have fatter tails than earthquakes and markets, suggesting an even more profound tendency to extremes. “History as seen from tail analysis,” Cirillo and Taleb conclude, “is far more risky, and conflicts far more violent than acknowledged by naive observation.”
Cirillo and Taleb also found no evidence that wars cluster together, as earthquakes and episodes of financial volatility are known to do. Rather, big wars follow no trend and simply occur with equal likelihood through time. Doing the statistics right, they argue, shows that the recent peaceful past is almost certainly causing us to seriously underestimate how much violent conflict we’re likely see in the future. I’ve given some more technical detail on the argument here. Some of this has been known since the 1960s (I wrote about the topic in a book 15 years ago), and other recent studies have found similarly dissenting views. European economists Mark Harrison and Nikolaus Wolf, for example, have looked at the total number of bilateral conflicts between nations going back to 1870, finding that the total number of such conflicts has actually been increasing from then to the present. Indeed, the number of countries at war at any given time has steadily been rising.
There are at least two overarching mental models for looking at the world: One could be called the bell curve and the other, the 80/20 curve.
When I was marketing my book, The End of Jobs, I spent a week sending personal emails (in Gmail, one by one, not in bulk) to two hundred people who I thought could potentially be in the top 1% of my readers, the people most excited about the book.
In total, I spent about 50% of my marketing resources on 1% of readers.
[That is the 80/20 model of how the world works. That suggests spending 80% of the money on the top 20% of the readers. Out of that 20% the 80/20 also applies. The top .04% (20% of 20%) would be the ultimate top. That is where he chose to spend his money.]
The 80/20 curve applies in any system when a small number of inputs account for a large percentage of outputs, which, as it turns out, is pretty much always.
[The bell curve model of the world applies when things are truly random – like the distribution of height in people.]
The professor then goes on to explain why Taylor Swift should price her tickets at around $40 (what most people are willing to pay), in order to maximize sales.
Looking at that chart, this makes sense.
That’s what most people would say, and it’s what business people would say. It is the bell-curve-model-of-the-world answer.
Let’s look at that exact same group of people through the lens of an 80/20 curve:
In doing statistical analysis on something, one must first ask if things are truly random. Are they? Often they are not and that often means using the power-law distribution. The power-law distribution is responsible for the 80/20 rule. When it comes to people’s behavior then the power-law distribution (80/20 rule) is probably a good fit.
Ip begins his book two decades before that, in 1989, at a high-level conference on the topic of financial crises. (Personally I have been going to conferences on financial crises for 30 years.) He cites Hyman Minsky, who “for decades had flogged an iconoclastic theory of business cycles that fellow scholars had largely ignored.” Minsky’s theory is often summarized as “Stability creates instability”—that is, periods of safety induce the complacency and the mistakes that lead to the crisis. He was right, of course. Minsky (who was a good friend of mine) added something else essential: the rise of financial instability is endogenous, arising from within the financial system, not from some outside “shock.”
At the same conference, the famous former Federal Reserve Chairman Paul Volcker raised “the disturbing question” of whether governments and central banks “end up reinforcing the behavior patterns that aggravate the risk.” Foolproof shows that the answer is yes, they do.
Besides financial implosions, Ip reflects on a number of natural and engineering disasters, including flooding rivers, hurricane damage, nuclear reactor meltdowns, and forest fires, and concludes that in all of these situations, as well, measures were taken that made people feel safe, “and the feeling of safety allowed danger to re-emerge, often hidden from view.”
Foolproof: Why Safety Can Be Dangerous and How Danger Makes Us Safe: Greg Ip: 9780316286046: Amazon.com: Books
Foolproof was excellent and much more subtle and thought provoking than its subtitle “Why Safety Can Be Dangerous and How Danger Makes Us Safe” would lead you to think. Instead of a retread of the well known Peltzman effect (the idea that innovations design to enhance safety just lead to greater risk taking without necessarily increasing safety) the book is actually a subtle and wide-ranging exploration of when it is true, when it is not, and its implications (e.g., seatbelt—the original Peltzman claim—actually don’t have the effect because people forget they are wearing them so don’t actually alter their behavior much, but antilock breaks are something you directly engage with while driving and lead to less safe driving). The wide-ranging aspect is a substantial amount of economics which is Greg Ip’s speciality, especially the recent financial and eurozone crises, but also safety in areas like food, floods, wildfires, automobiles, airplanes and professional football. Although Ip somewhat heroically tries to extract some lessons from all of this, the real strength of the book is tying together disparate topics and making you realize that there are no easy answers to any of these questions. That said, I personally find myself generally more sympathetic to what Ip calls the engineers (i.e., the people who try to make innovations to increase safety) rather than the ecologists (i.e., the people who worry about preserving the ecosystem as a whole without disturbances like new safety innovations). But overall an exciting read and thought provoking whether or not you agree with every part of it.
Why violence spreads
Behavior is contagious. Studies have shown that watching someone yawn can make us yawn. Conference speakers who come after a nervous speaker can absorb the nervousness. Bad moods spread from boss to employee.
Researchers think violence is no different. Although it’s a somewhat recent area of focus — the Institute of Medicine held a workshop on the subject in 2012 — the evidence for contagion of criminal or dangerous behavior has lurked in academic research for decades.
Studies have shown that the aircraft hijackings of the 1970s were contagious. Product tampering — also contagious. So is highway speeding, rioting and even military coups. Contagion is especially pronounced in suicides.
Numerous studies have shown that suicides cluster, particularly among young people. It is known as the Werther effect, a term coined in the 1970s by sociologist David Phillips describing what happened after Johann Wolfgang von Goethe published “The Sorrows of Young Werther” in 1774.
This report isn’t exactly new. Check out the report below from 2013:
Simple mathematical law benchmarks human confrontations : Scientific Reports
Many high-profile societal problems involve an individual or group repeatedly attacking another – from child-parent disputes, sexual violence against women, civil unrest, violent conflicts and acts of terror, to current cyber-attacks on national infrastructure and ultrafast cyber-trades attacking stockholders. There is an urgent need to quantify the likely severity and timing of such future acts, shed light on likely perpetrators, and identify intervention strategies. Here we present a combined analysis of multiple datasets across all these domains which account for >100,000 events, and show that a simple mathematical law can benchmark them all. We derive this benchmark and interpret it, using a minimal mechanistic model grounded by state-of-the-art fieldwork. Our findings provide quantitative predictions concerning future attacks; a tool to help detect common perpetrators and abnormal behaviors; insight into the trajectory of a ‘lone wolf’; identification of a critical threshold for spreading a message or idea among perpetrators; an intervention strategy to erode the most lethal clusters; and more broadly, a quantitative starting point for cross-disciplinary theorizing about human aggression at the individual and group level, in both real and online worlds.
We have shown that both the severities and the timings of events in a wide range of systems, follow a power-law functional form. There are various practical prediction tools and policies that follow from our work, as we now discuss. …
“Two mathematicians went into the desert” … is not the start of a joke, but the reality of mathematical research. Mathematician Nathalie Vriend and her PhD student Mathew Arran have just returned from Qatar where they went to study sand dunes. Understanding the behaviour of dunes doesn’t just help us understand the desert, but also the behaviour of other materials made up grains, such as snow or sugar.
“We will go to a dune field and investigate the internal structure of these dunes using ground penetrating radar and localised sampling,” explained Vriend before her departure. Because Vriend and Arran are interested in the movement of grains, and particularly in avalanches, they will be looking at so-called barchan dunes — these have the familiar crescent shape that springs to mind when you think of the desert and, crucially, they travel fast. Being driven along by the wind a small barchan dune can travel around 20 metres per year, depositing itself in a completely new location after two to three years — that’s pretty quick for a dune.
“We want to understand two things,” explains Vriend. “The first are the granular processes. When a dune moves you get [an accumulation of sand grains] close to the crest that starts to avalanche, so you get layers of individual avalanches on the down-wind side. Secondly, we are interested in the big picture; how fast do dunes [as a whole] move and how do they interact with each other?” The micro and macro processes are connected of course, and this is exactly where the main question lies. “I’m interested in connecting the small processes at the grain scale with the large processes at the dune scale. There must be a relation between the two, but not much is known about it.”
But Syria’s biggest vulnerability was that it had no recent record of recovering from turmoil. Countries that have survived past bouts of chaos tend to be vaccinated against future ones. Thus, the best indicator of a country’s future stability is not past stability but moderate volatility in the relatively recent past. As one of us, Nassim Nicholas Taleb, wrote in the 2007 book The Black Swan, “Dictatorships that do not appear volatile, like, say, Syria or Saudi Arabia, face a larger risk of chaos than, say, Italy, as the latter has been in a state of continual political turmoil since the second [world] war.” ?
The divergent tales of Syria and Lebanon demonstrate that the best early warning signs of instability are found not in historical data but in underlying structural properties. Past experience can be extremely effective when it comes to detecting risks of cancer, crime, and earthquakes. But it is a bad bellwether of complex political and economic events, particularly so-called tail risks—events, such as coups and financial crises, that are highly unlikely but enormously consequential. For those, the evidence of risk comes too late to do anything about it, and a more sophisticated approach is required.?
“There are some geopolitical thinkers I respect who argue that all this could trigger a regime change in Russia. And others who argue that it will make Vladimir Putin even stronger and that he will want to double down on his policy of destabilizing Ukraine sooner rather than later. Putin does not strike me as being willing to step aside in the manner of a Boris Yeltsin. I doubt he will go gently into that good night. He is a wildcard on the geopolitical stage.”
The “this” referred to above is about low oil prices and the fact that China will be devaluing its currency soon. That big energy deal between Russia and China is in yuan. If China is forced to devalue its currency in order to respond to Japan, then that is going increase pain on Russia.
Concerning Russia, there is a threat of regime change, instability plus limited options. Sounds like revolution will soon enough start brewing in Russia unless Putin can somehow redirect everybody’s attention. And truly Putin is not kind of guy (so far) that is likely to go quietly in the night. Things are more likely to get worse before they get better.
Thoughts from the Frontline – On the Verge of Chaos [Excerpt]
Complexity and Collapse
Okay class, for those who want a little extra credit, I’m going to give you some extra reading and viewing. Lacy Hunt encouraged me to listen again to our friend Niall Ferguson’s speech entitled “Empires on the Edge of Chaos” (Note: the introduction is 10 minutes long and can be skipped. You know who Niall is. And there is considerable Q&A at the end, so the speech itself is roughly 40 to 45 minutes. But the Q&A has lots of laughs, which makes it worth it.) Or you can read this article by Niall in Foreign Affairs, which has much of the same content.
I want to repeat the two quoted paragraphs that opened this letter, along with one more from the Foreign Affairs article. (Again, all emphasis mine.)
Great powers and empires are, I would suggest, complex systems, made up of a very large number of interacting components that are asymmetrically organized, which means their construction more resembles a termite hill than an Egyptian pyramid. They operate somewhere between order and disorder – on “the edge of chaos,” in the phrase of the computer scientist Christopher Langton. Such systems can appear to operate quite stably for some time; they seem to be in equilibrium but are, in fact, constantly adapting. But there comes a moment when complex systems “go critical.” A very small trigger can set off a “phase transition” from a benign equilibrium to a crisis – a single grain of sand causes a whole pile to collapse, or a butterfly flaps its wings in the Amazon and brings about a hurricane in southeastern England.
Not long after such crises happen, historians arrive on the scene. They are the scholars who specialize in the study of “fat tail” events – the low-frequency, high-impact moments that inhabit the tails of probability distributions, such as wars, revolutions, financial crashes, and imperial collapses. But historians often misunderstand complexity in decoding these events. They are trained to explain calamity in terms of long-term causes, often dating back decades. This is what Nassim Taleb rightly condemned in The Black Swan as “the narrative fallacy”: the construction of psychologically satisfying stories on the principle of post hoc, ergo propter hoc.
Defeat in the mountains of the Hindu Kush or on the plains of Mesopotamia has long been a harbinger of imperial fall. It is no coincidence that the Soviet Union withdrew from Afghanistan in the annus mirabilis of 1989. What happened 20 years ago, like the events of the distant fifth century, is a reminder that empires do not in fact appear, rise, reign, decline, and fall according to some recurrent and predictable life cycle. It is historians who retrospectively portray the process of imperial dissolution as slow-acting, with multiple overdetermining causes. Rather, empires behave like all complex adaptive systems. They function in apparent equilibrium for some unknowable period. And then, quite abruptly, they collapse.
The single most commented-upon letter that I have written was called “Fingers of Instability.” Longtime readers know it well, and I would suggest new readers take the time. It contains extremely important concepts for understanding why financial markets can advance smoothly for so long, and then all of a sudden there is chaos. The fingers of instability distributed throughout the sand pile of the global economic system end up getting triggered by some event that may in itself be quite minor. Yes, there are many factors contributing to an unstable global sand economic pile (think massive global debt, wanton overleverage, mischievous central banks with immoderate views of their importance, etc., etc.), but it only takes that fateful final grain of sand, dropped on just the right spot in the pile, to bring the whole thing cascading down.
What Niall is talking about is something that goes far deeper than another financial crisis like the one we recently experienced. What he is pointing out is that countries in financial distress are more constrained than normal in their actions. They have less ability to respond to crises. And some countries in crisis react in very unpredictable ways. Let’s talk about a second-order problem stemming from the fact that Japan is doing what it feels is necessary to keep from suffering a deflationary collapse. Understand, I’m not being critical of the Japanese for taking the actions they have, because I simply don’t know what other choice they have. That’s what makes their situation so difficult.
Japan’s major economic competitors – Germany, Korea, and China – will all have to respond, or their businesses will lose competitive advantage. Okay, we have seen large-scale currency movements all our lives. We adjust. That’s what businesses do.
Except, China and Russia have just signed an agreement for Russia to export rather massive amounts of energy to China, and they will take payment in yuan rather than dollars. A yuan that is going to be falling in value against the dollar as China responds to Japan.
In an ideal world for Russia, the Russian central bank would simply take the Chinese currency and add it to their reserves. But that would trigger a rather large “oops” that was not in the equation when they signed that deal. The yuan they are going to get is going to be losing value on the international market, and Russia is going to need hard currency (i.e. dollars) to pay down its large dollar-denominated debt and buy equipment to maintain and increase its ability to produce energy. And that equipment is generally sold in dollars and not in renminbi.
Couple that situation with the real potential for oil to go below $70 and Russia would have significant budgetary problems. And as David Hale pointed out recently in a private letter, if the US and Iran actually settle their differences over nuclear armaments later this month and sanctions are lifted, that could bring another 1–1.5 million barrels of oil a day onto the world energy markets. (He suggests it would have the same effect as a $400 billion global tax cut.) Mexico is committed to increasing its output, as are other countries, including the US. Sub-$70 oil is not out of the question, and in a global recession we could touch $50 easily. And while that would be good for consumers everywhere, it would certainly put a strain on Russia and other oil-producing countries. In fact, the scenario portends a major crisis for Russia.
And while we’re not as worried about Venezuela or other smaller oil producers, Russia is a potential problem, simply because it is so unpredictable. As noted above, the Japanese population is willing to take a great deal of pain. I don’t think we can say the same thing about the Russians at this point.
There are some geopolitical thinkers I respect who argue that all this could trigger a regime change in Russia. And others who argue that it will make Vladimir Putin even stronger and that he will want to double down on his policy of destabilizing Ukraine sooner rather than later. Putin does not strike me as being willing to step aside in the manner of a Boris Yeltsin. I doubt he will go gently into that good night. He is a wildcard on the geopolitical stage.
Russia has been willing to let the ruble fall rather precipitously rather than supporting it with their dollar reserves, which they are saving for other purposes. Even though the Russian economic situation is deteriorating due to sanctions, the Russian people have so far seemed to tolerate the downturn. As noted in last week’s Outside the Box, the West in general and the US in particular are blamed for Russia’s woes multiple times daily in the Russian media. Given the unpredictability of the current Russian leadership, there is simply no way to guess the outcome. That should make you nervous.
The 2008 crisis demonstrated that the global economic system is far more connected than most imagined. There has been no real deleveraging since that time as nations everywhere have doubled down on deficits and debt. European banks are just as leveraged to sovereign debt as they were before the crisis hit.
The recent Geneva Report on global deleveraging highlighted what the authors termed the “fragile eight” countries of Brazil, Chile, Argentina, Turkey, India, Indonesia, Russia, and South Africa as an “important source of concern in terms of future debt trajectories.” China and the “fragile eight” could find themselves in the unwanted role of hosts to the next phase of the global leverage crisis, it warned.
The accumulation of household, corporate, and government debt in both the emerging and developed worlds has been made all the more troubling by stubbornly low and slowing growth rates. The global capacity to take on more debt is rapidly diminishing because of the combination of low growth and low inflation, if not outright deflation, that we are beginning to see in major countries.
There seems to be a stubborn unwillingness on the part of authorities to recognize the problems that come along with swelling sovereign debt. We are coming ever closer to the point at which countries are going to have difficulty raising debt at interest rates that makes sense, absent the ability to create a shock and awe campaign like Japan’s. And few countries (actually, none come to mind) have the ability to monetize their debt to the tune of 200% of GDP, as Japan is setting out to do, without causing a dramatic currency collapse.
I have this argument all the time with fellow analysts. I get that “austerity” in a deflationary or even disinflationary environment is not exactly pro-growth. And if a country’s debt is low and there is growth, then you can get away with increasing debt. But there is a limit to the amount of debt that a country can take on, and we are approaching it in country after country. This trend is not good for global economic growth or stability. The second-order unintended consequences, such as those Niall describes, are very difficult to contemplate.
The world is not going to come to an end. I will be writing this letter and hopefully you will be reading it in 10 years. But economies and markets are going to get more fragile and volatile in the meantime. This is not the time to be a full-throated bull in the equity markets. And given the potential dollar bull market, there is going to be pressure on most commodities. Corporate debt, especially high-yield debt, is priced for perfection. When I look out over the horizon, I simply don’t see perfection. At a minimum, you should not be long high-yield debt. And if you’re running a business, you should get all the debt you can, even if you bank the cash, at today’s low rates for as long a term as you can get it. Take advantage of this unbelievably forgiving debt environment.
In the days before the 2011 Tohoku quake and tsunami, which killed more than 18,000 people, seafloor instruments showed that the offshore fault responsible was chattering and slipping slowly. Similar slip preceded a quake on an offshore fault in Chile.
Those tantalizing hints led two respected earthquake experts to suggest in an opinion piece in the journal Science that better monitoring of the seafloor might someday identify reliable precursors to the world’s most destructive quakes — including the one that will strike someday off the coast of the Pacific Northwest.
“Whether earthquakes are predictable or not is still an open question,” wrote Emily Brodsky and Thorne Lay, of the University of California, Santa Cruz, “but perhaps there is now some cause for optimism.”
Shortly before the 2011 tsunami in Japan “the offshore fault responsible was chattering and slipping slowly.”
Since this blog is more about war than anything else, why am I concerned about earthquake prediction? Because wars and earthquakes are similar mathematically. They both work the same way. If I can better understand how to predict earthquakes then that might help in predicting wars. In this case the article confirmed what I pretty much already knew: A system will reached an unstable tipping point shortly before a crash. Recognizing that you have reached an unstable tipping point is the key to understanding that a crash is coming.
A tipping point is reached when something small can cause something big. In the case of earthquakes, normal earth movement will start to become amplified. At this point there is no big collapse yet but it is near. The area has reached a tipping point. Having plenty of remote sensors can help detect these abnormal movements.
In the case of war, think about what it would take for Russia and/or China to go war against America. We know for sure that one tiny little incident could easily blow up into a major war between China and America. Clearly China and America are at a major tipping point. There is zero doubt about that.
What about Russia and America?
It´s harder to see with Russia and America. Putin threw out some implied nuclear threats the other day if anyone messes with Russia. Presumably it would be over Ukraine. Russians leaders have thrown out quite a few nuclear threats since 2008. What would happen if America and Nato started helping Ukraine? What would happen if Nato started stationing troops in the Baltics? It´s possible that things could get out of hand. Also, the West is sanctioning Russia sending its economy toward the direction of a recession. And a recession could mean big trouble for Putin.
It appears that Russia and America are entering a tipping point but it´s not quite as sensitive as the China-America tipping point at this time. Given the western sanctions on Russia, in a couple of years the Russia-America tipping point could be just as sensitive as the China-America one.
There are countless methods of predicting what will happen next in the stock market. Technical traders have their charts, quant funds use specialized algorithms, and psychics have crystal balls. Many of their methods have failed quite spectacularly in the past, especially in the 2008 financial crisis.
With that in mind, researchers have turned to other methods of understanding the vagaries of financial markets. One idea is to model the market’s activity in the same way geophysicists model earthquakes. It seems to work, but what if it ends up working too well?
Seismic financial activity
The idea is that a financial market crash looks — mathematically speaking — kind of like an earthquake. Both tend to be self-perpetuating, meaning that they build on their own momentum, and are often followed by aftershocks. Indeed, the researchers found that between 84% and 88% of extreme market drops were caused by this “self-excitation.”
Also common to both is that extreme negative events are more common than normal statistical models would suggest, and in both cases, it’s these extremes that beget the biggest risks. In other words, it’s not the 3.0 magnitude quake that’s going to worry you, it is, as we Californians like to call it, The Big One.
And as I have said many times in the past, they are like wars too. If you think about financial crashes and wars as like earthquakes, then it frees up the mind. You will not remain stuck on stupid by thinking the future is just a linear projection of the past. These crashes don´t follow the normal distribution. They follow the power law distribution which has a nice, big, fat tail. Lots of room for big crashes. Also, the possibility of a great-power nuclear war opens up. It´s just a really big crash.