{"id":4189,"date":"2019-11-21T15:04:44","date_gmt":"2019-11-21T19:04:44","guid":{"rendered":"https:\/\/www.shortform.com\/blog\/?p=4189"},"modified":"2022-03-11T15:34:06","modified_gmt":"2022-03-11T19:34:06","slug":"extremistan","status":"publish","type":"post","link":"https:\/\/www.shortform.com\/blog\/extremistan\/","title":{"rendered":"Extremistan: Why Improbable Events Have a Huge Impact"},"content":{"rendered":"\n

What is Extremistan<\/a>? Where is it? Where does the word come from? What elements of our lives fall under the purview of Extremistan?<\/p>\n\n\n\n

Extremistan is a term coined by Nassim Nicholas Taleb<\/a> to explain the randomness and deviations from the mean of most social, man-made aspects of human society. The term was popularized by Taleb’s book The Black Swan<\/a><\/em>.<\/p>\n\n\n\n

We’ll cover what Extremistan is, how it differs from Mediocristan<\/a>, what kinds of events and characteristics come from the land of Extremistan, and why Extremistan often makes prediction impossible.<\/p>\n\n\n\n\n\n\n\n

Extremistan vs. Mediocristan<\/strong><\/h3>\n\n\n\n

To explain how and why Black Swans occur, Taleb coins two categories to describe the measurable facets of existence: Extremistan and Mediocristan. 
<\/p>\n\n\n\n

In Mediocristan, randomness is highly constrained, and deviations from the average are minor. <\/strong>Physical characteristics such as height and weight are from Mediocristan: They have upper and lower bounds, their distribution is a bell curve<\/a>, and even the tallest or lightest human being isn\u2019t much taller or lighter than the average. In Mediocristan, prediction is possible.<\/em>
<\/p>\n\n\n\n

In Extremistan, however, randomness is wild, and deviations from the average can be, well, extreme.<\/strong> Most social, man-made aspects of human society\u2014the economy, the stock market, politics\u2014hail from Extremistan: They have no known upper or lower bounds, their behavior can\u2019t be graphed on a bell curve, and individual events or phenomena\u2014i.e., Black Swans\u2014can have exponential impacts on averages.
<\/p>\n\n\n\n

Imagine you put ten people in a room. Even if one of those people is Shaquille O\u2019Neal, the average height in the room is likely to be pretty close to the human average (Mediocristan). If one of those people is Jeff Bezos, however, suddenly the wealth average changes drastically (Extremistan).<\/p>\n\n\n\n

Extremistan\u2014Where Black Swans Fly<\/strong><\/h4>\n\n\n\n

In the realm of Mediocristan, randomness is highly constrained (mild): There\u2019s only so much variation in the physical aspects of our world. Thus, in Mediocristan, <\/strong>Black Swans are (effectively) impossible<\/em><\/strong>.
<\/p>\n\n\n\n

In Extremistan, however, randomness is highly variable (wild): No matter how large your sample size for a given phenomenon, you can\u2019t produce a trustworthy average or aggregate picture because of the variation <\/em>in that phenomenon. In Extremistan, <\/strong>Black Swans are frequent<\/em><\/strong>.
<\/p>\n\n\n\n

The Contours of Extremistan<\/strong><\/h2>\n\n\n\n

Although one needs only an intuitive sense of phenomena like wealth and market returns to understand that they don\u2019t adhere to the same rules as phenomena like height and weight, throughout the book Taleb provides a robust theoretical and statistical scaffolding for his claims about the differences between Mediocristan and Extremistan. 
<\/p>\n\n\n\n

Because these discussions tend toward the technical and aren\u2019t essential for understanding Black Swans and their role in our lives, we at Shortform have decided to summarize them as an appendix. 
<\/p>\n\n\n\n

Unfairness in Extremistan<\/strong><\/h4>\n\n\n\n

As exemplified by figures like Beyonc\u00e9 and Jeff Bezos, social and economic advantages accrue highly unequally in Extremistan.
<\/p>\n\n\n\n

One reason for this disparity is the \u201csuperstar effect.\u201d Coined by economist Sherwin Rosen to describe the unequal distributions of income and prestige in Extremistan sectors like stand-up comedy, classical music, and research scholarship, the \u201csuperstar effect\u201d operates when marginal differences in talent yield massive rewards.
<\/p>\n\n\n\n

The superstar effect<\/a>, it\u2019s vital to note, is meritocratic\u2014that is, those with the most talent, even if they\u2019re only slightly more talented than their competitors, get the spoils. What a theory like Rosen\u2019s fails to take into account, however, is that all-important aspect of life in Extremistan: <\/strong>dumb luck<\/em><\/strong>.
<\/p>\n\n\n\n

Consider research scholarship for instance. Sociologist Robert K. Merton has observed that academics rarely read all the papers they cite; rather, they look at the bibliography of a paper they have <\/em>read and pick sources to cite more or less at random. 
<\/p>\n\n\n\n

Now imagine a scholar cites three authors at random. Then a second scholar cites those same three authors, because the first author cited them. Then a third does the same thing. Suddenly the three authors that have been cited are considered leaders in their field, all by dint of dumb luck.
<\/p>\n\n\n\n

The phenomenon identified by Merton\u2019s study has been called both \u201ccumulative advantage\u201d and \u201cpreferential attachment.\u201d These concepts describe the innate human tendency to flock to past successes, regardless of whether those successes are the product of merit or chance.<\/strong>
<\/p>\n\n\n\n

Although cumulative advantage\/preferential attachment provides a better account of unfairness than the superstar effect\u2014because it accounts for randomness in the distribution of advantage\/preference\u2014it still isn\u2019t a perfect theory of Extremistan unfairness. This is because, according to cumulative advantage\/preferential attachment, winners stay on top. Once an entity\u2014a company, an academic, a professional sports coach\u2014reaches a certain level of success<\/a>, cumulative advantage\/preferential attachments holds that that entity will continue <\/em>to be successful, because humans naturally favor past success. But this doesn\u2019t reflect reality.
<\/p>\n\n\n\n

For example, according to cumulative advantage\/preferential attachment, Apple will forever be the king of consumer electronics, and Google will forever own the Internet. But even a cursory knowledge of business history shows a belief like this to be misguided. Consider this: If you tracked the 500 largest U.S. companies from 1957 to 1997, you\u2019d discover that only 74 <\/em>lasted the full 40 years. Some ceased to exist by virtue of mergers, but most simply failed. In other words, even in Extremistan, giants can occasionally be toppled by dwarfs<\/strong>.
<\/p>\n\n\n\n

Nevertheless, despite the possibility of creative destruction, Extremistan is defined by extreme concentration<\/em>\u2014of prestige, income, capital, influence, size, or what have you. These concentrations create the <\/strong>appearance<\/em><\/strong> of stability\u2014larger, more powerful entities are more resilient\u2014but they actually create the potential for catastrophic black swans<\/strong>.
<\/p>\n\n\n\n

The example par excellence of the risks of concentration is the banking industry. The explosive growth and interrelation of the major global financial institutions were the catalysts for the Great Recession of 2008.
<\/p>\n\n\n\n

(Shortform note: The popularity of The Black Swan <\/em>is due, in large part, to Taleb\u2019s clairvoyance about the vulnerabilities of the financial industry. The book was published in April 2007, before the worst of the crisis, yet Taleb describes the contours of that crisis with eerie precision.)
<\/p>\n\n\n\n

The most far-reaching unfairness of Extremistan, however, more so than economic inequality<\/a>, is inequality in intellectual influence. As illustrated by Merton\u2019s citation example just above, intellectual influence can be a matter of dumb luck rather than ability or insightfulness. This problem becomes acute when we trust thought leaders\u2014\u201dexperts\u201d\u2014with our lives and livelihoods (see Chapter 4: The Scandal of Prediction).
<\/p>\n\n\n\n

The Limits of the Bell Curve<\/strong> 
<\/p>\n\n\n\n

The classic bell curve\u2014which is also called the \u201cGaussian distribution\u201d after German mathematician Carl Friedrich Gauss\u2014is an accurate description of Mediocristan phenomena, but it is dangerously misleading when it comes to Extremistan.
<\/p>\n\n\n\n

Consider human height, an eminently Mediocristan phenomenon. With every increase or decrease in height relative to the average, the odds of a person being that tall or short decline. For example, the odds that a person (man or woman) is three inches taller than the average is 1 in 6.3; 7 inches taller, 1 in 44; 11 inches taller, 1 in 740; 14 inches taller, 1 in 32,000.
<\/p>\n\n\n\n

It\u2019s important to note that the odds not only decline as the height number gets further and further away from the average, but they decline at an accelerating rate. For example, the odds of someone being 7\u20191\u201d are 1 in 3.5 million, but the odds of someone being just four inches taller are 1 in 1 billion, and the odds of someone being four inches taller than that <\/em>are 1 in 780 billion!
<\/p>\n\n\n\n

Now consider an Extremistan phenomenon like wealth. In Europe, the probability that someone has a net worth higher than 1 million euros is 1 in 62.5; higher than 2 million euros, 1 in 250; higher than 4 million, 1 in 1,000; higher than 8 million, 1 in 4,000; and higher than 16 million, 1 in 16,000. The odds decrease at a constant, rather than accelerating, rate<\/strong>, indicating that their distribution doesn\u2019t conform to a bell curve.<\/strong>
<\/p>\n\n\n\n

(Note: The European wealth statistics cited above aren\u2019t precise, but they illustrate the central point: that wealth is scalable<\/a> and does not look like a bell curve.)
<\/p>\n\n\n\n

The upshot is that in Extremistan, as the name suggests, extreme events have much better odds of occurring than in Mediocristan. Simply put, <\/strong>the bell curve does not apply<\/em><\/strong>.<\/strong>
<\/p>\n\n\n\n

In our contemporary moment, the most egregious misuse of bell curves can be found among economists and financial-industry analysts. Most economists, including many Nobel Prize\u2013winners, treat financial markets as though they hail from Mediocristan when, in fact, they\u2019re from Extremistan.
<\/p>\n\n\n\n

A stunning example of economists\u2019 misinterpretation of the market came in 1998, with the collapse of Long-Term Capital Management (LCTM), a hedge fund that included among its founding partners two Nobel Prize\u2013winners, Myron Scholes and Robert C. Merton (Robert K. Merton\u2019s son). Scholes and Merton won their Nobel Prize for a theory of stock option pricing; the theory, however, was based on a Gaussian model of the market that excluded the possibility of Black Swans.
<\/p>\n\n\n\n

When markets were disrupted by the Asian financial crisis of 1997 and the Russian financial crisis of 1998\u2014a one-two punch of Black Swans\u2014Scholes and Merton\u2019s theory was revealed for the fantasy it was. The twin crises resulted in a crushing $4.6 billion loss for LCTM in fewer than four months. The firm had to be bailed out by a consortium of private banks, at the behest of the Federal Reserve. 
<\/p>\n\n\n\n

The problem is that economists\u2019 models are thoroughly Platonified: self-consistent, but bearing almost no resemblance to reality. Economists are like philosopher John Locke\u2019s madmen: they reason \u201ccorrectly from erroneous premises.\u201d<\/strong>
<\/p>\n\n\n\n

Representing Randomness: Fractals and Power Laws<\/strong><\/h4>\n\n\n\n

So can the phenomena of Extremistan be modeled\u2014and thereby predicted\u2014at all?  Not precisely; but they can <\/em>be approximated\u2014by the use of fractals<\/em>.
<\/p>\n\n\n\n

Developed by mathematician Beno\u00eet Mandelbrot in the 1970s, \u201cfractals\u201d are Mandelbrot\u2019s coinage for geometric patterns that repeat at different scales. Fractals, unlike pure geometric shapes like triangles or circles, are seen quite frequently in nature. For example, a leaf\u2019s veins look like little branches, and a tree\u2019s branches look like little trees: the basic shape of the tree is echoed at the smaller scales.
<\/p>\n\n\n\n

The reason fractals are helpful in representing Black Swans is that their internal ratios stay constant across scales. Unlike bell curves, in which ratios decline at accelerating rates the further one gets from the average, fractals exhibit no (or mild) acceleration. They obey power laws<\/a><\/em>, which describe a functional relationship between two quantities in which the relationship remains constant no matter what the initial size of the quantities.
<\/p>\n\n\n\n

Take the European wealth example noted just above. As the wealth number doubled, the incidence decreased by 4x (wealth greater than 1 million: 1 in 62.5; wealth greater than 2 million: 1 in 250; wealth greater than 4 million: 1 in 1,000; etc.). The \u201cpower\u201d in this relationship is 2, because 2^2 (2 squared) is 4. 
<\/p>\n\n\n\n

Now, imagine the power was 1: Each time the wealth doubled, the incidence would only decrease by 2x (2^1=2). The probability of extraordinary wealth would increase<\/strong>.
<\/p>\n\n\n\n

For Extremistan phenomena, the power laws aren\u2019t known with any certainty, but they can be approximated. Say, for example, you want to assess the risk of a stock portfolio, and you know that, based on past data, the worst-case scenario is a -5% move once every 2 years. With a power of 2\u2014remember that the power is estimated\u2014you can assume that a -10% move will happen once every 8 years (2^2=4) and a -20 percent move will happen once every 32 years. (For scale, in the 1987 crash, the U.S. stock market lost almost 23% of its value, an impossibility<\/em> according to Gaussian economic models.) With fractal\/power-law distributions, a 1000-year flood can become a 100-year one, and a 100-year one can become a 10-year one<\/strong>.
<\/p>\n\n\n\n

When we begin to analyze Extremistan in terms of the fractal<\/a> paradigm, some Black Swans suddenly become \u201cgray\u201d\u2014they\u2019re not predictable with any sort of precision, but they are, at least, imaginable<\/em>.  <\/p>\n","protected":false},"excerpt":{"rendered":"

What is Extremistan? Where is it? Where does the word come from? What elements of our lives fall under the purview of Extremistan? Extremistan is a term coined by Nassim Nicholas Taleb to explain the randomness and deviations from the mean of most social, man-made aspects of human society. The term was popularized by Taleb’s book The Black Swan. We’ll cover what Extremistan is, how it differs from Mediocristan, what kinds of events and characteristics come from the land of Extremistan, and why Extremistan often makes prediction impossible.<\/p>\n","protected":false},"author":4,"featured_media":4203,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[24,25],"tags":[60],"class_list":["post-4189","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-society","category-statistics","tag-black-swan","","tg-column-two"],"yoast_head":"\nExtremistan: Why Improbable Events Have a Huge Impact - Shortform Books<\/title>\n<meta name=\"description\" content=\"Extremistan is a term coined by Nassim Nicholas Taleb to explain the randomness and deviations from the mean of most man-made aspects of human society.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.shortform.com\/blog\/extremistan\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Extremistan: Why Improbable Events Have a Huge Impact\" \/>\n<meta property=\"og:description\" content=\"Extremistan is a term coined by Nassim Nicholas Taleb to explain the randomness and deviations from the mean of most man-made aspects of human society.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.shortform.com\/blog\/extremistan\/\" \/>\n<meta property=\"og:site_name\" content=\"Shortform Books\" \/>\n<meta property=\"article:published_time\" content=\"2019-11-21T19:04:44+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-03-11T19:34:06+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.shortform.com\/blog\/wp-content\/uploads\/2019\/11\/black-swan-extremistan.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"779\" \/>\n\t<meta property=\"og:image:height\" content=\"518\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Amanda Penn\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Amanda Penn\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"9 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.shortform.com\/blog\/extremistan\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.shortform.com\/blog\/extremistan\/\"},\"author\":{\"name\":\"Amanda Penn\",\"@id\":\"https:\/\/www.shortform.com\/blog\/#\/schema\/person\/01b0e4c9ddb993e51d03808839d538b0\"},\"headline\":\"Extremistan: Why Improbable Events Have a Huge Impact\",\"datePublished\":\"2019-11-21T19:04:44+00:00\",\"dateModified\":\"2022-03-11T19:34:06+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.shortform.com\/blog\/extremistan\/\"},\"wordCount\":1980,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.shortform.com\/blog\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.shortform.com\/blog\/extremistan\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.shortform.com\/blog\/wp-content\/uploads\/2019\/11\/black-swan-extremistan.jpg\",\"keywords\":[\"The Black Swan\"],\"articleSection\":[\"Society\",\"Statistics\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.shortform.com\/blog\/extremistan\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.shortform.com\/blog\/extremistan\/\",\"url\":\"https:\/\/www.shortform.com\/blog\/extremistan\/\",\"name\":\"Extremistan: Why Improbable Events Have a Huge Impact - 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