Are You Smart? So Why Aren’t You Rich?
Well..
The distribution of wealth follows a well-known pattern called the Pareto Principle, also known as the 80:20 rule, which states that 80 percent of results flow from 20 percent of causes. Indeed, this report concluded that just 10% of the population take hold of 83% of the world’s wealth. Not the exact numbers, but you got the gist of it.
Pareto principle is a well-studied pattern that crops up in a wide range of social phenomena. Yet the wealth distribution is still among the most controversial because of the issues it raises about fairness and equality. How could so few people have so much wealth?
The traditional answer is that we live in a meritocracy in which people are rewarded on the basis of their ability; be it talent, intelligence, effort, and so on. Which, over time, translates into the current wealth distribution.
But there is a slight problem with this idea: while wealth distribution follows the 80:20 rule, the distribution of human skills generally follows a normal distribution (the bell curve) that is symmetric about an average value. For example, intelligence, as measured by IQ tests. Average IQ is 100, but nobody has an IQ of 1,000 or 10,000.
The same is true of effort, as measured by hours worked. Some people work more hours than average and some work less, but nobody works a billion times more hours than anybody else.
And yet when it comes to the rewards for those intelligence and effort, some people do have billions of times more wealth than other people.
What factors, then, determine how individuals become wealthy? Could it be that chance plays a bigger role than anybody expected?
The Answer.
A little while back I stumbled upon the work of Alessandro Pluchino and a couple of his colleague at the University of Catania, Italy. They have successfully made a model called “Talent vs Luck” (TvL) model, which mimics the evolution of careers of a group of people over a working period of 40 years and realistically quantify the role of luck and talent in successful careers.
In this respect, Pluchino and Co effectively generalize the definition of ”talent” by identifying it with ”any personal quality which enhances the chance to grab an opportunity”. In other words, by the term ”talent” they broadly mean intelligence, skill, smartness, stubbornness, determination, hard work, risk taking, and so on.
The result is quite exceptional. Their simulations accurately reproduce the wealth distribution in the real world and provide us with a theory where the advantage of having a great talent is a necessary, but not a sufficient condition to reach a very high degree of success. Ordinary people with an average level of talent are statistically destined to be successful much more than the most talented ones, provided that they are more blessed by fortune along their life.
The Model, Explained.
They consider N=1000 individuals, with talent Ti (intelligence, skills, ability, etc.) normally distributed in the interval [0, 1] around a given mean mT with a standard deviation σT, so that some people are more talented than average and some are less so, but nobody is orders of magnitude more talented than anybody else.
The agent Ak are randomly placed in fixed positions within a square world and surrounded by a certain number of events NE of lucky ones, green circles, with relative percentage pL; and unlucky ones, red circles, with percentage (100-pL) which moves across the world following random trajectories, which will ensure that different individuals are exposed to different amount of lucky or unlucky events during their life, regardless of their own talent.
The talent is distributed just like other distribution seen for various human skills, or even characteristics like height or weight. Some people are taller or smaller than average, but nobody is the size of an ant or a skyscraper. After all, we are all quite similar.
Then, for a single simulation run, a working life period P of 40 years (from the age of twenty to the age of sixty) is considered, with a time step δt equal to six months. At the beginning of the simulation, all agents are endowed with the same amount Ci of capital, representing their starting level of success/wealth. This choice has the evident purpose of not offering any initial advantage to anyone, meaning everyone has the same starting point in life in terms of capital.
In the simulation, there are three different possible actions for a given agent Ak:
- No event-point intercepts the position of agent Ak: this means that no relevant facts have happened during the last six months; agent Ak does not perform any action.
- A lucky (green) event intercepts the position of agent Ak: this means that a lucky event has occurred during the last six month; as a consequence, agent Ak doubles her capital/success with a probability proportional to her talent Tk. It will be Ck(t) = 2Ck(t − 1) only if rand[0, 1] < Tk, which means only if agent is smart enough to profit from his/her luck.
- An unlucky event intercepts the position of agent Ak: this means that an unlucky event has occurred during the last six month; as a consequence, agent Ak halves her capital/success, i.e. Ck(t) = Ck(t − 1)/2.
These rules (including the choice of dividing by a factor of 2 the initial capital in case of unlucky events and doubling it in case of lucky ones, proportionally to the agent’s talent), are intentionally simple and can be considered widely shareable, since they are based on the common sense evidence that success, in everyone life, has the property to both grow or decrease very rapidly.
Furthermore, these rules gives a significant advantage to highly talented people, since they can make much better use of the opportunities offered by luck (including the ability to exploit a good idea born in their brains). On the other hand, a car accident or a sudden disease, for example, are always unlucky events where talent plays no role.
The Results.
At the end of the 40 years simulation, Pluchino and Co rank the individuals by wealth and study the characteristics of the most successful. They also calculate the wealth distribution, and then repeat the simulation many times to check the robustness of the outcome.
When the team rank individuals by wealth, the distribution is exactly like that seen in real-world societies, which follows Pareto’s ”80:20” rule, since 20% of the population owns 80% of the total capital, while the remaining 80% owns the 20% of the capital.
That may not be surprising or unfair if the wealthiest 20 percent turn out to be the most talented. But that isn’t what happens. The wealthiest individuals are typically not the most talented or anywhere near it, as the maximum success never coincides with the maximum talent, and vice-versa.
Here, it is evident that the most successful individuals are not the most talented ones. In fact, the most successful agent, with Cmax = 2,560, has a talent only slightly greater than the mean value mT = 0.6, while the most talented one has a capital/success lower than C = 1 unit, much less of the initial capital C(0) = 10 unit.
So if not talent, what other factor causes this skewed wealth distribution?
In the simulation, the team shows this by ranking individuals according to the number of lucky and unlucky events they experience throughout their 40-year careers.
Clearly, good luck made the difference. And, if it is true that the most successful agent has had the merit of taking advantage of all the opportunities presented to him (in spite of his average talent), it is also true that if your life is as unlucky and poor of opportunities as that of the other agent, even a great talent becomes useless against the fury of misfortune.
It is evident that the most successful individuals are also the luckiest ones, and the less successful individuals are also the unluckiest ones.
Summary.
What has been found up to now is that, in quantitative terms, that a great talent is not sufficient to guarantee a successful career and that, instead, less talented people are very often able to reach the top of success — another ”stylized fact” frequently observed real life.
The key point, which intuitively explains how it may happen that moderately gifted individuals achieve (so often) far greater honors and success than much more talented ones, is the hidden and often underestimated role of luck, as resulting from the simulations.
In fact, following the dynamical rules of the TvL model, a talented individual theoretically has a greater probability to reach a high level of success than a moderately gifted one, since they have a greater ability to grasp any opportunity that comes. But well of course, luck has to help them in yielding those opportunities.
Therefore, from the point of view of a single individual, we could conclude that, while it is impossible (by definition) to control the occurrence of lucky events; the best strategy to increase the probability of success (at any talent level) is to broaden the personal activity, the production of ideas, the communication with other people, while seeking for diversity and mutual enrichment.
In other words, to be an open minded person, always ready to be in contact with others, in order to be exposed to the highest probability of lucky events (and exploit it by means of the personal talent).
On the other hand, from the macro point of view of the entire society, the probability to find moderately gifted individuals at the top levels of success is greater than that of finding the very talented ones, because moderately gifted people are much more numerous and, with the help of luck, have — globally — a statistical advantage to reach a great success, in spite of their lower individual probability.
Sources:
[1] Koch, Richard. The 80/20 Principle. 2011. Accessed: January 15, 2020.
[2] Credit Suisse. Global Wealth Report. 2019. Accessed: January 15, 2020.
[3] Emerging Technology from the arXiv. If you’re so smart, why aren’t you rich? Turns out it’s just chance. 2018. Accessed: January 15, 2020.
[4] A. Pluchino, A. E. Biondo, & A. Rapisarda. Talent vs Luck:
the role of randomness in success and failure. 2018. Accessed: January 15, 2020.
