This turns out to be a very difficult question to answer just by looking at individuals. We all know stories of ambitious and talented people like Steve Jobs or Bill Gates, who grew companies and created great wealth. But for each one of these superstars, there may have been many more people who were equally ambitious and talented, yet did not succeed. Maybe the string of investment and managerial decisions that made one person’s company successful, and that seem so very wise in retrospect, were actually just the entrepreneurial equivalent of flipping a coin 20 times and getting all heads. The chances of that happening are about 1 in 1 million, so if enough people try it, someone is bound to get lucky and look like a coin-flipping genius—purely by chance. [...]
To illustrate the basic idea, suppose that we are flipping coins and trying to figure out whether they are fair or biased. This is tricky with only a single coin. If we flip it 20 times and get 14 heads versus 6 tails, we might be a little suspicious that it’s biased. But we could not be completely sure: The chance of a fair coin yielding 14 heads or more is still about 6 percent, and unlikely events do sometimes come to pass. A much better approach would be to perform the same 20-flip experiment with thousands of identical coins: If we still see lots of them coming up with an overabundance of heads, then something is definitely fishy. [...]
Or is it? The obvious objection, of course, is that the coin-flip investment game is a gross oversimplification of reality. For example, it takes no account of consumption—the money that rich people siphon out of the market to spend on travel, penthouses, yachts, or whatever. Nor does it allow for the fact that some people are born with inherited wealth that gives them a huge head start in life. Yet it turns out that neither consumption nor inherited advantages make much of a difference: Even when the model is adjusted to allow for such factors, Pareto still rules. Another possible objection is that it may take a very long time for the wealth distribution to converge to its steady state. However, it has been shown both numerically and experimentally that the convergence to the Pareto wealth distribution is actually quite fast. [...]
Still, it is possible to get a crude sense of the effect of talent by modifying the investment game to include two types of players. Normal investors are just like those in the first game: They flip a coin with heads yielding a return of 30 percent, and tails producing a loss of 10 percent. But the talented investors are more skilled at playing the market: They earn slightly more than 30 percent when the coin comes up heads, and lose slightly less than 10 percent when the coin comes up tails. Now we set the players loose and ask an empirical question: How big can this “talent differential” be and still stay statistically consistent with the power law wealth distribution we see in the real world?
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