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IQ is normalized, but that doesn't change the shape of the distribution. It changes the scale, but not the shape. I agree there's a lot of details that need to

by dhfhduk 10y ago

IQ is normalized, but that doesn't change the shape of the distribution. It changes the scale, but not the shape. I agree there's a lot of details that need to be done to make this more rigorous, and I was hoping that the article would be more thorough. But this has been on my mind a lot lately. Basically, most human [behavioral] traits are normally distributed, or something close to it, which is radically different from income distributions. At some point, the shape of an income distribution must become inconsistent with what we know about the shape of human trait distributions and wages under fair labor markets, etc. It should be possible to test whether or not an income distribution is consistent with a given trait and market model, and to compare them statistically. I appreciate McCardle's writing, and read that in the past, but think it's sort of tangential to the points being raised here. Furthermore, many of her arguments aren't supported by the data. That is, income inequality really exists across a wide range of professions. If anything, I suspect there's some demographic effects involved (for example, older, very well-established individuals with a "lock" in a given labor market, shutting out younger individuals). They also don't even get into cheating as another factor that's nonrandom and might be construed as a "skill" but is arguably unrelated to "real" market value. All of this is consistent with arguments that the biggest predictor of returns is length in the market. That is, you're better off putting things in a very diversified index portfolio than anything else. Someone else mentioned Buffet. Even if things were random, with enough people, you'd still end up with people who look like they're not benefiting randomly. Anyway, I'm not really trying to question Buffet's investing skill. I'm sure that it's not totally random, but I suspect that there is a big element of randomness also. And income per se is different from investment skill per se.

ikeboy 10y ago
>IQ is normalized, but that doesn't change the shape of the distribution. It changes the scale, but not the shape. It means talking about an IQ of 5 million as somehow analogous to linear extrapolations of height or age means the author has no clue what they're talking about. The only way to have an IQ that high is to have a population large enough for it to be meaningful, while the other example are possible statistically (if not physically). Anyway, having now read through the rest of the article, my critique is much simpler: they're using a simplified model with specific magic constants, and using it to derive exact values for other unknowns (specifically talent). >Half the time it will come up heads and yield a return of 30 percent, and on the rest of the tosses it will come up tails and yield a loss of 10 percent. The numbers are chosen to give an average annual return of 10 percent, plus or minus 20 percent, which is typical of investments in the real stock market, but the overall conclusions do not depend on these specific numbers. But then they say >How big can this “talent differential” be and still stay statistically consistent with the power law wealth distribution we see in the real world? >It turns out that it can’t be more than about 1 percent. I haven't dug into the numbers here, but I'm comfortable discounting their conclusion because of the clear signs of unfamiliarity with concepts mentioned, as above. Also, they seem to be assuming that most of these people made their money investing, but that's unrealistic, yet they cite articles about money managers. It may very well be that money managers perform randomly, but that clearly shouldn't extrapolate to other rich people. The whole model is incorrect, people get rich by doing many other things (start a business, invent a product, etc) many (most?) of which are, in fact, related to talent but are completely missed by the model. They casually throw out the claim that "They cannot possibly be the whole story at the high end, where people’s wealth is primarily determined by capital gains or losses on investments." but with no citation, and, as above, I doubt that. (A quick search turns of up http://www.forbes.com/sites/erincarlyle/2013/09/18/how-self-made-forbes-400-billionaires-earned-their-money/ http://www.forbes.com/sites/erincarlyle/2013/09/18/how-self-... which says investing is plurality but not a majority of the top 400's sources of wealth). They keep on going back to people like Gates and Jobs, further confusing the question.

by dhfhduk 10y ago

ikeboy 10y ago

>IQ is normalized, but that doesn't change the shape of the distribution. It changes the scale, but not the shape. It means talking about an IQ of 5 million as somehow analogous to linear extrapolations of height or age means the author has no clue what they're talking about. The only way to have an IQ that high is to have a population large enough for it to be meaningful, while the other example are possible statistically (if not physically). Anyway, having now read through the rest of the article, my critique is much simpler: they're using a simplified model with specific magic constants, and using it to derive exact values for other unknowns (specifically talent). >Half the time it will come up heads and yield a return of 30 percent, and on the rest of the tosses it will come up tails and yield a loss of 10 percent. The numbers are chosen to give an average annual return of 10 percent, plus or minus 20 percent, which is typical of investments in the real stock market, but the overall conclusions do not depend on these specific numbers. But then they say >How big can this “talent differential” be and still stay statistically consistent with the power law wealth distribution we see in the real world? >It turns out that it can’t be more than about 1 percent. I haven't dug into the numbers here, but I'm comfortable discounting their conclusion because of the clear signs of unfamiliarity with concepts mentioned, as above. Also, they seem to be assuming that most of these people made their money investing, but that's unrealistic, yet they cite articles about money managers. It may very well be that money managers perform randomly, but that clearly shouldn't extrapolate to other rich people. The whole model is incorrect, people get rich by doing many other things (start a business, invent a product, etc) many (most?) of which are, in fact, related to talent but are completely missed by the model. They casually throw out the claim that "They cannot possibly be the whole story at the high end, where people’s wealth is primarily determined by capital gains or losses on investments." but with no citation, and, as above, I doubt that. (A quick search turns of up http://www.forbes.com/sites/erincarlyle/2013/09/18/how-self-made-forbes-400-billionaires-earned-their-money/ http://www.forbes.com/sites/erincarlyle/2013/09/18/how-self-... which says investing is plurality but not a majority of the top 400's sources of wealth). They keep on going back to people like Gates and Jobs, further confusing the question.