The growth of the well-being of individuals occurs only due to a series of successful circumstances including https://argoprep.com/blog/k8/what-is-a-multiple/ – abilities and talent do not affect financial success in any way.
Researchers from the University of Catania (Italy) have carried out mathematical modeling of the enrichment process in human society. It turned out that the greatest wealth is achieved not by the most talented and capable, but by quite mediocre “players”. The only thing that distinguishes them from their poorer “colleagues” is go math grade 7 their increased luck in the course of economic interactions. The text of the corresponding article is available on the Cornell University preprint server.
The authors of the new work used the method of agent-based modeling to study the process of welfare growth. In total, the “behavior” of thousands of economic agents (“people”) was modeled, each of which had a certain level of development of abilities that influenced his chances of successful economic interactions with other agents.
Ability indicators for example https://argoprep.com/blog/k8/go-math-grade-6-vs-argoprep/ had a normal (bell-shaped) distribution. In other words, the overwhelming majority of agents (67%) had average abilities, but there were both very talented and completely untalented “players”. The researchers note that this distribution corresponds to modern ideas about the real distribution of intelligence and private abilities among people.
The agents in the model were themselves motionless (which reflects the position of people in the real economy or other branches of social life), but faced moving “events”. Some of them (green) turned out to be happy and led to an increase in the welfare of the agent who faced him. Others – red – on the contrary, led to ruin. In theory, the distribution of collisions with favorable and unfavorable events should be uniform, but in practice this happens only with an unlimited amount of time of the model’s existence. However, for the experiment, the number of agents, the time of their existence and the course of events was limited (as in real life), so someone got too many successful events, and someone too many unsuccessful ones.
As a result, after 40 years of simulated time, about 80 percent of all wealth within the model ended up in the hands of 20 percent of the agents, and another 20 percent in the hands of the remaining 80 percent of the agents. The authors believe this is consistent with the distribution observed in the real world. This, however, is not entirely correct – it would be more accurate to say that such a distribution is observed in most countries of the “golden billion”. At the same time, in third world countries, the distribution tends to be slightly more uneven.
Most interestingly, the agents with the highest level of “ability” for cost-effective interactions did not turn out to be the majority of the richest 20 percent. The ability level of the “super-rich” was only slightly above average.
From this, the researchers drew a number of practical conclusions. For example, in some cases it is more rational not to distribute funding for certain scientists based on their earlier successes – and this is exactly what happens, de facto, in the grant system, which takes into account the number of highly cited works previously written by a given scientist. On the contrary, it will be most effective to distribute grants evenly among all scientists, regardless of their citation and past achievements. Similarly, one should not always invest in the most successful companies now – “luck” can turn away from them at the next stage of development of a particular market sector.