Pareto Principle Examples and History

Economics consists of theoretical laws which nobody has verified and of empirical laws which nobody can explain.
—Michal Kalecki

For a very long time, the Pareto law has lumbered the economic scene like an erratic block on the landscape; an empirical law which nobody can explain.
—Josef Steindl

In the book that I’ve been writing on keeping up in the information age (subscribe via email to receive a copy when it’s finished), I’ve touched on both Sturgeon’s Law (“90% of everything is crap”) and the Pareto principle, as part of a section on filtering information. But I needed a good example. So here we are.

The main idea behind the Pareto principle, sometimes called the 80-20 rule, is that 80% of the effect of something comes from 20% of the cause. Or more broadly, it’s the principle of the “vital few and trivial many.” A few things make most of the difference.

example-of-pareto-principleOh, and, by the way, if this is the first time you’ve been exposed to this concept, the amount of value you’ll get out of having it in your cognitive toolkit is, well, to quote the Beastie Boys, “it’s wack,” yo. I suspect the Pareto principle obeys the Pareto principle — that is, you can get 80% cognitive value out of 20% of concepts, and the Pareto principle is one of those 20%.

So, consider dating, for instance. (Relevant given the continued popularity of my earlier post on prolonged eye contact.)

When it comes to dating, considering the Pareto principle, we should expect that 80% of the value of all dating advice, techniques, etc. can be had from only 20% of the tips. And I think this is true. In fact, I’m pretty confident that all dating wisdom can be boiled down to six words: approach more of the opposite sex, or maybe just two: approach more.

(In fact, I think you could model relationships satisfactorily via Markov processes, but that’s a separate post.)

Real Examples of the Pareto Principle

So, okay, right, now you know what the Pareto principle is all about, which brings me to my main motivation for writing this, which is: what’s a cool empirical example of the Pareto principle in action? The dating example is okay, but it’s also more-or-less fabricated from whatever imagination is made out of.

Empirical is perhaps the wrong word. What we want are examples with rigor. Maybe we actually live in some bizarre world where there’s a 1:1 correspondence between the value you get out of dating advice and the amount you read, such that 80% of the advice gives 80% of the value.

Or maybe we live in a world where the more you know about dating, the more valuable the next piece you learn becomes — since you have more context or something. In that case, the last 20% might be worth 80% of the value, via some clearly Satanic reverse Pareto principle.

So, real examples.

  • Wikipedia would have you believe that the Pareto principle was born during Vilfredo Pareto’s study of Italian landowners — 20% of them owned 80% of the land.

  • The article alternatively suggest that it stemmed out of the study of pea pods — that Pareto noticed 20% of the pea pods in his garden produced 80% of the peas.

Which of these is true? Probably neither.

Looking past this deep seated and shocking inequality in the pea kingdom, the reality of the discovery of the Pareto principle is not so clear cut. The principle itself was not so much the discovery of Pareto, but Joseph Juran, who repurposed some of Pareto’s ideas. He writes about this in a 1975 paper, “The non-Pareto principle; mea culpa”:

The Pareto principle as a universal was not original with Pareto.

Where then did the universal originate? To my knowledge, the first exposition was by myself. Had I been structured along different lines, assuredly I would have called it the Juran principle. However, I was not structured that way. Yet I did need a shorthand designation, and I had no qualms about Pareto’s name. Hence the Pareto principle.

More examples:

Which makes me wonder: could you get 80% of the value of this article by reading 20% of the words?

Worldbuilding, Worldbuilders, and Mathematics

This week, I was introduced to the hobby of worldbuilding — inventing imaginary places, making maps, elaborating histories. (The platonist in me prefers to think of worldbuilding as the discovery of fictional universes, rather than an act of invention.)

Tolkien

There is a (perhaps apocryphal) tale that J. R. R. Tolkien got into a fight with his publisher over using the words “elves” and “dwarves” instead of “elfs” and “dwarfs”. The publisher argued that the latter was how the dictionary did it. “I know,” Tolkien responded, “I wrote the dictionary.” Tolkien had, in fact, spent several years as an assistant working on the Oxford English Dictionary.

Although most known for his fiction, Tolkien was a linguist at heart, even inventing some eleven fictional languages along with a number of variations on those languages.

The remarkable degree of internal consistency of some Tolkien’s language use in The Lord of the Rings is perhaps unsurprising, then. The prefix “mor” in his work translates literally to black and is used consistently — Mordor is black land, moria is black pit, and morranon is black gate. The “dor” in Mordor means land. Gondor, as you might expect, means stone land.

Of his languages and Lord of the Rings, Tolkien wrote “The invention of languages is the foundation. The ‘stories’ were made rather to provide a world for the languages than the reverse.”

Foundations

It’s very far away,
It takes about half a day
to get there
if we travel by my, uh, dragonfly.
—Jimi Hendrix, “Spanish Castle Magic”

I have no such patience for languages. I have little interesting in learning a new one, except perhaps Lojban, and less still in attempting to invent my own, unless we’re speaking of programming.

But it does suggest a question: Where would I start with discovering a fictional universe? If I wanted to maximize the believability of a fictional universe, on what rock would I put it?

I’m thinking maybe economics. Robin Hanson recently pointed out that the movie Her, while enjoyable, is far from realistic. Humans invent human-level “strong” AI and use it… to chat with.

I doubt that’s how it’s going to play out in the real world. Why bother hiring a human to do any sort of computer work when an AI can do it faster, better, and cheaper? Newspaper reporter? Computer has it covered. Secretary? Computer. Author? Computer. Researcher? Computer. Teacher? Computer. Customer support? Computer.

Talk about a fuck up. In the real world, everything makes a perverted sort of sense. A causes B causes C, ad infinitum. In the real world, physics makes the rules, and we, well, we’re an expression of them. When worldbuilding, there is no physics ensuring that what you write is consistent. It’s up to you.

Discovering a coherent world draws on the same skills that are necessary for understanding our own world. When the movie Gravity was released, it was criticized for fucking up a whole lot of physics — vehicles in impossible orbits, backpacks with unlimited fuel supplies, and indestructible space suits.

That’s all ignoring messy details like relationship mechanics, attraction, and how language works. The movie Ted drives me up the wall — not because there is a magical, talking teddy bear, but because Mark Wahlburg and Mila Kunis’s relationship strikes me as absurd. A chick like that, decent career, and she’s with this unemployed man-child? Ri-ght.

All of which is to suggest that the skills and knowledge necessary to understand this world are the same needed to build your own: economics, game theory, physics, social dynamics, and so on. The converse is true, too: to understand this world, consider the sort of things you’d need to know to build your own. Or, as Feynman put it, “What I cannot create, I do not understand.”

The Fractal Nature of Worldbuilding

Worldbuilders often go out of their way to produce natural looking maps — like by spilling coffee on paper. Here’s an example:

coffee-stain-world

Another technique for generating maps: taking pictures of rusted fire hydrants.

world-building-rusted-fire-hydrant

But there’s a whole branch of mathematics for this sorta thing, fractals! Ever notice the self-similar nature of trees? Each branch looks like a small tree unto itself. Or coastlines — each “crevice” of a coastline itself looks like a coastline. Branches, snowflakes, crystals — all like this.

Indeed, ever after reading Benoit Mandelbrot’s The Fractal Geometry of Nature, I sometimes catch myself seeing fractals superimposed on clouds when I unfocus my eyes.

Mathematics and Worldbuilding

Okay, confession: I wasn’t 100% honest with you. While this is my first brush with groups of other worldbuilders, I’ve toyed with the idea in the past — after colliding with Tegmark’s mathematical universe hypothesis and reading Permutation City.

I wasn’t thinking about making maps. I was wondering: How could I model the essentials of emergent behavior? Is it Conway’s game of life — or something simpler? How could I simulate a universe? What do the fundamental laws of our universe look like?

And I started wondering if mathematics wasn’t a sort of world unto itself. A set of axioms with implications of the sort we could never anticipate — implications we are still discovering, who knows what it could lead to? And not one system of axioms, but infinitely many — each with different definitions, objects, theorems, branches, and applications.

In short, I started to think of the work of a mathematician as being a whole lot like worldbuilding. Discovering some object that obeys certain rules of logic and nothing more, and asking, “What does it do? Is such and such true of this thing? How does it behave here?”

I’m reminded of János Bolyai. Of non-euclidean geometry, he wrote, “Out of nothing I have created a strange new universe.”

The Life Satisfaction of Economists

Tyler Cowen has written a post on a paper about the life satisfaction of economists. It’s a horrible paper. I don’t like it at all.

Here are some reasons:

  • The authors use satisfaction and happiness interchangeably. They are not the same construct and it will confuse those not familiar with the existing literature.
  • The sample is taken from a few mailing lists of European economists.
  • The study measures life satisfaction with a single question.
  • The life satisfaction question is part of a broader survey focused on scientific misbehavior, which means that such information is going to be primed before the life satisfaction question.
  • Meditation: Imagine that you conduct two studies: one in which you ask participants to reflect on all the good things that have happened to them in the past three months, followed by a life satisfaction question, and one in which you just ask them about life satisfaction. Is there a difference?
  • I remain unconvinced that numeric ratings of life satisfaction can be meaningfully compared across populations. The French rate themselves as less healthy than Americans, but live an average of 3 years longer.

Still not convinced? The Maasai are a semi-nomadic African people in Kenya and the average Maasai is as satisfied as the economists in this study.

The Terrible Future Isn’t: Drone Delivery Edition

Last night, Amazon’s CEO Jeff Bezos appeared on 60 Minutes and spoke about the possibility of using drones to deliver small packages (“drone delivery“). My gut reaction is the engineer’s natural skepticism: I’ll believe it when he’s rolled out something that works instead of touting vaporware. (Remember hyperloop? Yeah, that’s never going to happen.) That’s not so fun to read about, though, so let’s instead talk about the promise of drone delivery.

The setup: imagine that anything a drone can carry can be delivered to your door within 30 minutes of purchase, provided that someone has it within ten miles of your location.

My initial thought, given that I have yet to eat breakfast, is food delivery. You don’t order meals through Amazon because you don’t want to wait two days when you’re hungry. Given that there are already businesses — pizza delivery, for one — in this market, I could see it happening. Indeed, if drones become easy and cheap enough that small businesses can afford them, we could see scenarios where women working from home make fresh food (cookies or lasagna or what-have-you) to order via the internet. Chefs working from home and delivering meals via drone could disrupt the restaurant industry.

More prosaically, if you’re out of bagels or you need some fresh oregano for the dish you’re planning on making for dinner, you could have a drone fly you some from the grocery store. Or maybe if you need a suit dry-cleaned or a package shipped, a drone could come and pick up the goods.

I could see this changing the operation of libraries, too, where you can order a library book online and then have it delivered to you via drone. The same goes for prescription medication.

There are certain things that people want to replace as quickly as possible: television remotes, specialty drill bits, and internet routers. If you have a pet reptile, you’ll know that when their sunning lamp burns out, you want to replace it pronto. These sort of things would be fine candidates for drone delivery.

Another interesting potential is the ability to deliver goods to places other than houses. If you’re out camping and forgot to bring hot dogs, a drone could fly out to your location. Maybe something like this would work for broken down cars, too, although I’m not sure what you might order. A blanket or hot chocolate if your car is stuck in the snow, maybe.

I’ve seen some talk of this changing the way drug deals go down because it would eliminate the risk of a face-to-face transaction. I’m not completely convinced of this, though, because a police officer could just order drugs online and then follow the drone back to wherever it came from after delivery. It might still be safer, though.

Anyways, the focus here has been on incremental improvement and the disappearance of chores. If drones do pan out, though, the interesting effects are going to be in how they disrupt markets and enable new types of trade. We can imagine trying to predict the consequences of the internet or the telephone when they were first introduced. The changes wrought were no doubt much larger than anyone expected. I don’t think drones are as fundamental as either of those, but I do think that — should the technology come to fruition — the results will be quite different from what we anticipate.

Criticism of Economics

I don’t have the requisite expertise to lay out compelling criticism of economics as a whole, and I suspect such an endeavor would be profitless (heh). The thrust of such an argument, though — its quintessence — is captured in this quote by Richard Feynman:

See, I have the advantage of having found out how hard it is to get to really know something, how careful you have to be about checking the experiments, how easy it is to make mistakes and fool yourself. I know what it means to know something and therefore, I see how they get their information and I can’t believe that they know it.

A useful heuristic I employ (among others) when evaluating the trustworthiness of knowledge is to ask myself the question, “How confident am I that this will still be true in fifteen years?” Note the progress and effectiveness of the natural sciences, e.g. physics, when compared with the softer sciences, e.g. psychology. The results of physics are solid. You can build on the knowledge. Building on psychology, on the other hand, is building on top of a swamp; constructing a home on quicksand.

Now, economics is more like quicksand than concrete, and most economic reasoning is vulnerable to dismissals based on this. You might say something like: well, such and such assumption is untenable. The world is too complex to be boiled down and understood via simple economic models.

The problem with such arguments, with the skeptic dismissal, is that they’re a means of filtering out just the things that you don’t like. If you read an economic argument that you don’t like, you say, “Boo! Economics!” and dismiss it outright, instead of engaging with it.

Further, even though economics doesn’t work all that well, there are no good alternatives. You can have either not terribly effective models or no models at all, and you’re going to be much better off trying to reason with some model than no model.

Right, so what I’m getting at: it’s a failure mode to take economics too seriously, but it’s another failure mode to dismiss it entirely. There is a middle way; one must reach a certain Zen understanding of the limits of knowledge.