80:20 rule: 80 percent of the wealth is owned by 20 percent of the people. Indeed, a report last year concluded that just eight men had a total wealth equivalent to that of the world’s poorest 3.8 billion people.
This seems to occur in all societies at all scales. It is a well-studied pattern called a power law that crops up in a wide range of social phenomena. But the distribution of wealth is among the most controversial because of the issues it raises about fairness and merit. Why should so few people have so much wealth?
The conventional answer is that we live in a meritocracy in which people are rewarded for their talent, intelligence, effort, and so on. Over time, many people think, this translates into the wealth distribution that we observe, although a healthy dose of luck can play a role.
But there is a problem with this idea: while wealth distribution follows a power law, the distribution of human skills generally follows a normal distribution that is symmetric about an average value. For example, intelligence, as measured by IQ tests, follows this pattern. 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 this work, some people do have billions of times more wealth than other people. What’s more, numerous studies have shown that the wealthiest people are generally not the most talented by other measures.
What factors, then, determine how individuals become wealthy? Could it be that chance plays a bigger role than anybody expected? And how can these factors, whatever they are, be exploited to make the world a better and fairer place?
Today we get an answer thanks to the work of Alessandro Pluchino at the University of Catania in Italy and a couple of colleagues. These guys have created a computer model of human talent and the way people use it to exploit opportunities in life. The model allows the team to study the role of chance in this process.
The results are something of an eye-opener. Their simulations accurately reproduce the wealth distribution in the real world. But the wealthiest individuals are not the most talented (although they must have a certain level of talent). They are the luckiest. And this has significant implications for the way societies can optimize the returns they get for investments in everything from business to science.
Pluchino and co’s model is straightforward. It consists of N people, each with a certain level of talent (skill, intelligence, ability, and so on). This talent is distributed normally around some average level, with some standard deviation. So some people are more talented than average and some are less so, but nobody is orders of magnitude more talented than anybody else.
This is the same kind of 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. Indeed, we are all quite similar.
The computer model charts each individual through a working life of 40 years. During this time, the individuals experience lucky events that they can exploit to increase their wealth if they are talented enough.
However, they also experience unlucky events that reduce their wealth. These events occur at random.