One analysis of the NLSY in Intelligence, Genes, and Success is of particular interest since it questions Herrnstein and Murray’s conclusion that criminal activity is associated with low IQ. Sociologist Lucinda Manolakes reanalyzes of criminal activity as a function of IQ, race, parental education and some other variables. She claims that there is an interaction between race and IQ that implies the chance of being criminally active increases with IQ for black makes, the opposite of the trend for white males.
There are a few problems though. She added some novel variables to her analysis including environment (urban, Rural, etc) and she did not state how the final results depend on these factors. This could be an old data “dredging” trick: add and subtract background variables and interactions from a model until you get the “right” answer for the variables you are interested in, here an IQ and race interaction. I have done this way too much myself. Also, from her equations I obtained the following logistic regression coefficients for IQ .0233 (SE=.0065) for whites and 0.0167 (SE=.0066) for black. So both coefficients are positive, significant (p < 0.01), and going in the same direction indicating that the relationship between IQ and crime is not reversed for whites and blacks. I might be missing something though but I can not tell unless I replicate the analysis.
Her analysis also has an interesting non-racial result: an interaction between IQ and parental education. The likelihood that a dumb child (lowest third of the IQ distribution) is criminally active increases with parental educational., That is, dumb children of college graduates are more criminally active then dumb children of high school drop outs. Maybe it is because college graduates do not spank.
Sunday, November 9, 2008
Saturday, November 1, 2008
Wages: Sucks to be poor and white, good to be smart and black, but stupidity is always a problem
Herrnstein and Murray look at wages directly and indirectly by looking at prestige of occupation in The Bell Curve and claim that holding IQ steady that blacks are more likely to be in prestigious occupations and blacks make similar wages to whites by occupation groups. There models are not very complicated, however, and they do not test for differences in return for IQ and other factors nor do they use the standard method of modeling wages with the log transformation. In Intelligence, Genes, and Success, Cavello, Elabaddi, and Heeb (CEH) and Cawley, Connerly, Heckman, and Vytalacil (CCHV) look at wages directly to test Herrnstein and Murray conclusions with more complicated models that use the standard log transformation of wages.
CCHV fit a separate regressions for each gender-race combination (black-males, black females, Hispanic males, etc) on log wages over time as a function of “g” and the nine other principle components of the intelligence test and some background variables (experience, experience squared, unemployment rate). They conclude that “g” exists, has the same attributes in all the race gender combinations, and is a very good predictor of wages, though not the only good predictor. This is all consistent with the Bell Curve although you can quibble about the size of “g” predictive effect. They then make a more startling claim. After, rejecting the null hypothesis that all the coefficients for all the gender-race combinations are the same they then declare “payment is not made for ‘ability’ alone”, that is, there is no meritocracy. Besides the fact that there model building is not transparent (why not unemployment rate squared) they have a technical problem that with a large data set (over 20,000 observations) it is easy to reject null hypotheses (get small p-values) for a very small differences that may not be very meaningful. You have to actually look at the way and the size the coefficients differ. When you actually look at the coefficients for IQ (“g” is this case) you see that the return for IQ is always higher for black males and females than white males and females. This means that in many cases blacks with a given IQ are making more than whites with the same IQ. The authors do not tell us what to make of this evidence but they do quote Ecclesiastes so I am sure they felt pretty smug.
CER do a better job of detangling the interactions between gender, race, and IQ. They refit Herrnstein and Murray’s model but find a fairly convincing age, race, and IQ interaction. Specifically, the return on IQ for black females is much higher than that for white females or either white or black makes for that matter. They also model the log wages and find the same thing as CCHV, higher returns on IQ for black then for whites, particularly black females. They conclude by testing certain linear combinations that the “average” black male does make %6 less then the comparable white man, but for women this is reversed with “average” black women making 15% more then the comparable white women. The male result does not contradict the differences in return of IQ, it just means that whites with black like characteristics (below white average IQ, low SES, low education attainment, average black age) make more than blacks. The black advantage on the return of IQ is made up somewhat by the higher white male return for age. The opposite is true for females. Another result is that white males have a higher return for socio economic status than black males: poor whites have a greater disadvantage to rich whites then poor blacks do rich blacks. CER do not seem smug, but they also do not discuss these differences. The obvious answer is reverse discrimination in both in males (supported by the SES findings but contradicted by the age finding) and females (supported by all variables), but it could also be an artifact of measurement error.
None of these authors ask a related but non-racial question. Is the return on IQ similar in all occupation groups or for all levels of education? Does a dumb high school dropout garbage man make less than a brainiac drop out garbage man? Maybe the later is better at fighting off the Raccoons. Herrnstein and Murray cite two economists that do look at this with the NLSY: Blackburn and Neumark. You have to wade through a lot of weird econometrics to get at it, but their provocative answer appears to be no. They write, “The increase in the return for education has occurred largely for workers of higher levels of ‘academic ability’[IQ]”. The conclusion is that for some of us spending 8 years at community college has no advantage over spending 8 years working at Burger King. If they are right than maybe we should leave a few children behind.
CCHV fit a separate regressions for each gender-race combination (black-males, black females, Hispanic males, etc) on log wages over time as a function of “g” and the nine other principle components of the intelligence test and some background variables (experience, experience squared, unemployment rate). They conclude that “g” exists, has the same attributes in all the race gender combinations, and is a very good predictor of wages, though not the only good predictor. This is all consistent with the Bell Curve although you can quibble about the size of “g” predictive effect. They then make a more startling claim. After, rejecting the null hypothesis that all the coefficients for all the gender-race combinations are the same they then declare “payment is not made for ‘ability’ alone”, that is, there is no meritocracy. Besides the fact that there model building is not transparent (why not unemployment rate squared) they have a technical problem that with a large data set (over 20,000 observations) it is easy to reject null hypotheses (get small p-values) for a very small differences that may not be very meaningful. You have to actually look at the way and the size the coefficients differ. When you actually look at the coefficients for IQ (“g” is this case) you see that the return for IQ is always higher for black males and females than white males and females. This means that in many cases blacks with a given IQ are making more than whites with the same IQ. The authors do not tell us what to make of this evidence but they do quote Ecclesiastes so I am sure they felt pretty smug.
CER do a better job of detangling the interactions between gender, race, and IQ. They refit Herrnstein and Murray’s model but find a fairly convincing age, race, and IQ interaction. Specifically, the return on IQ for black females is much higher than that for white females or either white or black makes for that matter. They also model the log wages and find the same thing as CCHV, higher returns on IQ for black then for whites, particularly black females. They conclude by testing certain linear combinations that the “average” black male does make %6 less then the comparable white man, but for women this is reversed with “average” black women making 15% more then the comparable white women. The male result does not contradict the differences in return of IQ, it just means that whites with black like characteristics (below white average IQ, low SES, low education attainment, average black age) make more than blacks. The black advantage on the return of IQ is made up somewhat by the higher white male return for age. The opposite is true for females. Another result is that white males have a higher return for socio economic status than black males: poor whites have a greater disadvantage to rich whites then poor blacks do rich blacks. CER do not seem smug, but they also do not discuss these differences. The obvious answer is reverse discrimination in both in males (supported by the SES findings but contradicted by the age finding) and females (supported by all variables), but it could also be an artifact of measurement error.
None of these authors ask a related but non-racial question. Is the return on IQ similar in all occupation groups or for all levels of education? Does a dumb high school dropout garbage man make less than a brainiac drop out garbage man? Maybe the later is better at fighting off the Raccoons. Herrnstein and Murray cite two economists that do look at this with the NLSY: Blackburn and Neumark. You have to wade through a lot of weird econometrics to get at it, but their provocative answer appears to be no. They write, “The increase in the return for education has occurred largely for workers of higher levels of ‘academic ability’[IQ]”. The conclusion is that for some of us spending 8 years at community college has no advantage over spending 8 years working at Burger King. If they are right than maybe we should leave a few children behind.
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