The Bell Curve: Intelligence and Class Structure in American Life
Page 38
Our finding that wage differentials nearly disappear may be a surprise especially in light of the familiar conclusion that wage disparities persist even for blacks and whites with the same education. For example, in the 1992 national data collected by the Bureau of the Census, median earnings of year-round, full-time workers in 1992 were $41,005 for white male graduates with a bachelor’s degree and only $31,001 for black males with the same degree.15 Similar disparities occur all along the educational range. The same pattern is found in the NLSY data. Even after controlling for education, blacks in the NLSY still earned only 80 percent of the white wage, which seems to make a prima facie case for persistent discrimination in the labor market.
Blacks and whites who grow up in similar economic and social circumstances likewise continue to differ in their earning power as adults. This too is true of the NLSY data. Suppose we control for three factors—age, education, and socioeconomic background—that are generally assumed to influence people’s wages. The result is that black wages are still only 84 percent of white wages, again suggesting continuing racial discrimination.
And yet controlling just for IQ, ignoring both education and socioeconomic background, raises the average black wage to 98 percent of the white wage and reduces the dollar gap in annual earnings from wages for year-round workers to less than $600. A similar result is given as the bottom row in the following table, this time extracting as well the effects of different occupational distributions between whites and blacks. The rows above it show what happens when separate wages are computed for different occupational groupings. Black Wages as a Percentage of White Wages, 1989
Occupation Controlling Only for Age Controlling for Age and Education Controlling for Age, Education, and Parental SES Controlling Only for Age and IQ
Professional/technical 87 92 95 102
Managers/administrators 73 72 74 82
Clerical workers 99 97 101 119
Sales workers 74 74 77 89
Craft and kindred workers 81 80 83 96
Transport operatives 88 87 90 108
Other operatives 80 80 84 100
Service workers 92 96 102 119
Unskilled laborers 67 69 72 84
All employed persons 80 82 86 98
The table contains a number of noteworthy particulars, but the most interesting result, which generalizes to every occupational category, is how little difference education makes. A common complaint about wages is that they are artificially affected by credentialism. If credentials are important, then educational differences between blacks and whites should account for much of their income differences. The table, however, shows that knowing the educational level of blacks and whites does little to explain the difference in their wages. Socioeconomic background also fails to explain much of the wage gaps in one occupation after another. That brings us to the final column, in which IQs are controlled while education and socioeconomic background are left to vary as they will. The black-white income differences in most of the occupations shrink considerably. Altogether, the table says that an IQ score is more important—in most cases, much more important—in explaining black-white wage differences than are education and socioeconomic background for every occupational category in it.
Analyzing the results in detail would require much finer breakdowns than the ones presented in the table. Why is there still a meaningful differential in the managers/administrators category after controlling for IQ? Why do blacks earn a large wage premium over whites of equivalent age and IQ in clerical and service jobs? The explanations could have something to do with ethnic factors, but the varieties of jobs within these categories are so wide that the differentials could reflect nothing more than different ethnic distributions in specific jobs (for example, the managers/administrators category includes jobs as different as a top executive at GM and the shift manager of a McDonalds; the service workers category includes both police and busboys). We will not try to conduct those analyses, though we hope others will. At the level represented in the table, it looks as if the job market rewards blacks and whites of equivalent cognitive ability nearly equally in almost every job category.
Although we do not attempt the many analyses that might enrich this basic conclusion, one other factor—gender—is so obvious that we must mention it. When gender is added to the analysis, the black-white differences narrow by one or two additional percentage points for each of the comparisons. In the case of IQ, this means that the racial difference disappears altogether. Controlling for age, IQ, and gender (ignoring education and parental SES), the average wage for year-round black workers in the NLSY sample was 101 percent of the average white wage.
Annual Income and Poverty
We turn from wages to the broader question of annual family income. The overall family income of a 29-year-old in the NLSY (who was not still in school) was $41,558 for whites, compared to only $29,880 for blacks and $35,514 for Latinos. Controlling for cognitive ability shrinks the black-white difference in family income from $11,678 to $2,793, a notable reduction, but not as large as for the wages discussed above: black family income amounted to 93 percent of white family income after controlling for IQ. Meanwhile, mean Latino family income after controlling for IQ was slightly higher than white income (101 percent of the white mean). The persisting gap in family income between blacks and whites is reflected in the poverty data, as the figure below shows. Controlling for IQ shrinks the difference between whites and other ethnic groups substantially but not completely.
Controlling for IQ cuts the poverty differential by 77 percent for blacks and 74 percent for Latinos
If commentators and public policy specialists were looking at a 6 percent poverty rate for whites against 11 percent for blacks—the rates for whites and blacks with IQs of 100 in the lower portion of the graphic—their conclusions might differ from what they are when they see the unadjusted rates of 7 percent and 26 percent in the upper portion. At the least, the ethnic disparities would look less grave. But even after controlling for IQ, the black poverty rate remains almost twice as high as the white rate—still a significant difference.16 Why does this gap persist, like the gap in total family income, while the gaps in educational attainment, occupations, and wages did not? The search for an answer takes us successively further from the things that IQ can explain into ethnic differences with less well understood roots.17
ETHNIC DIFFERENCES ON INDICATORS OF SOCIAL PROBLEMS
Ethnic differences in poverty persist, albeit somewhat reduced, after controlling for IQ. Let us continue with some of the other signs of social maladjustment that Part II assessed for whites alone, adding ethnic differences to the analysis. We will not try to cover each of the indicators in those eight chapters (Appendix 6 provides much of that detail), but it may be instructive to look at a few of the most important ones, seeing where IQ does, and does not, explain what is happening behind the scenes.
Unemployment and Labor Force Participation
Black unemployment has been higher than white unemployment for as long as records have been kept—more than twice as high in 1992, typical of the last twenty years.18 Once again the NLSY tracks with the national statistics. Restricting the analysis to men who were not enrolled in school, 21 percent of blacks spent a month or more unemployed in 1989, more than twice the rate of whites (10 percent). The figure for Latinos was 14 percent. Controlling for cognitive ability reduces these percentages, but differently for blacks and Latinos. The difference between whites and Latinos disappears altogether, as the figure below shows; that between whites and blacks narrows but does not disappear. Black males with an IQ of 100 could expect a 15 percent chance of being unemployed for a month or more as of 1989, compared with an 11 percent chance for whites. Dropping out of the labor force is similarly related to IQ. Controlling for IQ shrinks the disparity between blacks and whites by 65 percent and the disparity between Latinos and whites by 73 percent.19
After controlling for IQ, the ethnic discrepancy in male unemployment shrinks
by more than half for blacks and disappears for Latinos
Scholars are discussing many possible explanations of the poorer job outcomes for black males, some of which draw on the historical experience of slavery, others on the nature of the urbanizing process following slavery, and still others on the structural shifts in the economy in the 1970s, but ethnic differences in IQ are not often included among the possibilities.20 Racism and other historical legacies may explain why controlling for IQ does not eliminate differences in unemployment and dropping out of the labor force, but, if so, we would be left with no evident explanation of why such factors are not similarly impeding the equalization of education, occupational selection, or wages, once IQ is taken into account. With the facts in hand, we cannot distinguish between the role of the usual historical factors that people discuss and the possibility of ethnic differences in whatever other personal attributes besides IQ determine a person’s ability to do well in the job market. We do not know whether ethnic groups differ on the average in these other ways, let alone why they do so if they do. But to the extent that there are such differences, controlling for IQ will not completely wash out the disparities in unemployment and labor force participation. We will not speculate further along these lines here.
Marriage
Historically, the black-white difference in marriage rates was small until the early 1960s and then widened. By 1991, only 38 percent of black women ages 15 to 44 were married, compared to 58 percent of white women.21 In using the NLSY, we will limit the analysis to people who had turned 30 by the time of the 1990 interview. Among this group, 78 percent of whites had married before turning 30 compared to only 54 percent of blacks. The white and Latino marriage rates were only a few percentage points apart. When we add cognitive ability to the picture, not much changes. According to the figure below, only 8 percent of the black-white gap disappears after controlling for IQ, leaving a black with an IQ of 100 with a 58 percent chance of having married by his or her thirtieth birthday, compared to a 79 percent chance for a white with the same IQ.
The reasons for this large difference in black and white marriage have been the subject of intense debate that continues as we write. One school of thought argues that structural unemployment has reduced the number of marriageable men for black women, but a growing body of information indicates that neither a shortage of black males nor socioeconomic deprivation explains the bulk of the black-white disparity in marriage.22 As we have just demonstrated, neither does IQ explain much. For reasons that are yet to be fully understood, black America has taken a markedly different stance toward marriage than white and Latino America.
Controlling for IQ explains little of the large black-white difference in marriage rates
Illegitimacy
A significant difference between blacks and whites in illegitimate births goes back at least to the early part of this century. As with marriage, however, the ethnic gap has changed in the last three decades. In 1960, 24 percent of black children were illegitimate, compared to only 2 percent of white children—a huge proportional difference. But birth within marriage remained the norm for both races. By 1991, the figures on illegitimate births were 68 percent of all births for blacks compared to 39 percent for Latinos and 18 percent for non-Latino whites.23 The proportional difference had shrunk, but the widening numerical difference between blacks and whites had led to a situation in which births within marriage were no longer the norm for blacks, while they remained the norm (though a deteriorating one) for whites.
The black-white disparity in the NLSY is consistent with the national statistics (although somewhat lower than the latest figures, because it encompasses births from the mid-1970s to 1990). As of the 1990 interview wave, the probabilities that a child of an NLSY woman would be born out of wedlock (controlling for age) were 62 percent for blacks, 23 percent for Latinos, and 12 percent for non-Latino whites. As far as we are able to determine, this disparity cannot be explained away, no matter what variables are entered into the equation. The figure below shows the usual first step, controlling for cognitive ability.
Controlling for IQ reduced the Latino-white difference by 44 percent but the black-white difference by only 20 percent. Nor does it change much when we add the other factors discussed in Chapter 8: socioeconomic background, poverty, coming from a broken home, or education. No matter how the data are sliced, black women in the NLSY (and in every other representative database that we know of) have a much higher proportion of children out of wedlock than either whites or Latinos. As we write, the debate over the ethnic disparity in illegitimacy remains as intense and as far from resolution as ever.24 We can only add that ethnic differences in cognitive ability do not explain much of it either.
Controlling for IQ narrows the Latino-white difference in illegitimacy but leaves a large gap between blacks and whites
Welfare
As of 1991, about 21 percent of black women ages 15 to 44 were on AFDC nationwide, compared to 12 percent of Latino women and 4 percent of white women (including all women, mothers and nonmothers). 25 The NLSY permits us to ask a related question that extends back through time: How many of the NLSY women, ages 26 to 33 as of 1990, had ever been on welfare? The answer is that 49 percent of black women and 30 percent of all Latino women had been on welfare at one time or another, compared to 13 percent of white women.26 The figure shows the effects of controlling for IQ.
Adding cognitive ability explains away much of the disparity in welfare recipiency among blacks, whites, and Latinos. In the case of Latinos, where 84 percent of the difference disappears, the remaining disparity with whites is about three percentage points. The disparity between blacks and whites—30 percent of black women receiving welfare, compared to about 12 percent for whites—is still large but only half as large as the difference not adjusted for IQ.
Controlling for IQ cuts the gap in black-white welfare rates by half and the Latino-white gap by 84 percent
This is as much as we are able to explain away. When we probe further, IQ does not do more to explain the black-white difference. For example, we know that poverty is a crucial factor in determining whether women go on welfare. We therefore explored whether IQ could explain the black-white difference in a particular group of women: those who had had children and had been below the poverty line in the year prior to birth. The results of the analysis are shown in the figure below. Among women who were poor in the year prior to birth, the black-white difference is slightly larger after controlling for IQ, not smaller. These data, like those on illegitimacy and marriage, lend support to the suggestion that blacks differ from whites or Latinos in their likelihood of being on welfare for reasons that transcend both poverty and IQ, for reasons that are another subject of continuing debate in the literature.27
Low-Birth-Weight Babies
Low birth weight, defined as infants weighing less than 5.5 pounds at birth, is predictive of many subsequent difficulties in the physical, social, and cognitive development of children. Historically, blacks have had much higher rates of low birth weight than either Latinos or whites. In the most recent reporting year ( 1991 ) for national data, almost fourteen percent of all black babies were low birth weight, compared to five percent of white babies and six percent of Latino babies. 28 In our analyses of the NLSY data, we focus on babies who were low birth weight relative to the length of gestation, excluding premature babies who were less than 5.5 pounds but were appropriate for gestational age using the standard pediatric definition.29 Using unrounded data, the rate of low-birth-weight births for blacks (10 percent) was 2.9 times as high as for whites. The Latino rate was 1.5 times the white rate. The figure shows what happens after controlling for IQ. The black rate, given an IQ of 100, drops from 10 percent to 6 percent, substantially closing the gap with whites.30 The Latino-white gap remains effectively unchanged.
Even among poor mothers, controlling for IQ does not diminish the black-white disparity in welfare recipiency
Children Living in Poverty
Controlling for IQ cuts the black-white disparity in low-birth-weight babies by half
The Child’s Home Environment
We now turn to the measure of the home environment, the HOME index, described in Chapter 10. For this and the several other indexes used in the assessment of NLSY children, we follow our practice in Chapter 10, focusing on children at the bottom of each scale, with bottom operationally defined as being in the bottom 10 percent.