Ethnic Inequalities in Relation to IQ - The National Context - The Bell Curve: Intelligence and Class Structure in American Life - Richard J. Herrnstein, Charles Murray

The Bell Curve: Intelligence and Class Structure in American Life - Richard J. Herrnstein, Charles Murray (1996)

Part III. The National Context

Chapter 14. Ethnic Inequalities in Relation to IQ

Ethnic differences in education, occupations, poverty, unemployment, illegitimacy, crime , and other signs of inequality preoccupy scholars and thoughtful citizens. In this chapter, we examine these differences after cognitive ability is taken into account.

We find that Latinos and whites of similar cognitive ability have similar social behavior and economic outcomes. Some differences remain, and a few are substantial, but the overall pattern is similarity. For blacks and whites, the story is more complicated. On two vital indicators of success—educational attainment and entry into prestigious occupations—the black-white discrepancy reverses. After controlling for IQ, larger numbers of blacks than whites graduate from college and enter the professions. On a third important indicator of success, wages, the black-white difference for year-round workers shrinks from several thousand to a few hundred dollars.

In contrast, the B/W gap in annual family income or in persons below the poverty line narrows after controlling for IQ but still remains sizable. Similarly, differences in unemployment, labor force participation, marriage, and illegitimacy get smaller but remain significant after extracting the effect of IQ. These inequalities must be explained by other factors in American life. Scholars have advanced many such explanations; we will not try to adjudicate among them here, except to suggest that in trying to understand the cultural, social, and economic sources of these differences, understanding how cognitive ability plays into the mix of factors seems indispensable. The role of cognitive ability has seldom been considered in the past. Doing so in future research could clarify issues and focus attention on the factors that are actually producing the more troubling inequalities.

America’s pressing social problems are often portrayed in ethnic terms. Does the nation have an unemployment problem? It depends. Among whites in the recession year of 1992, unemployment was under seven percent, but it was fourteen percent among blacks.1 Poverty? The poverty rate in 1992 for whites was less than twelve percent but thirty-three percent for blacks.2 Such numbers, and the debate over what they should mean for policy, have been at the center of American social policy since the early 1960s. As Latinos have become a larger portion of the population, the debate has begun to include similar disparities between Latinos and whites.

Such disparities are indisputable. The question is why. Surely history plays a role. Open racism and institutional discrimination of less obvious sorts have been an important part of the historical story for blacks and are relevant to the historical experience of Latinos and Asian-Americans as well. Cultural differences may also be involved. An ethnic group with a strong Roman Catholic heritage, such as Latinos, may behave differently regarding birth control and illegitimacy than one without that background. The tradition of filial respect in the Confucian countries may bear on the behavior of American teenagers of East Asian ancestry when one looks at, for example, delinquency.

Part II showed the impact of cognitive ability on poverty, illegitimacy, crime, and other social problems in America among whites. Chapter 13 showed that the major ethnic groups in America differ, on the average, in cognitive ability. There is accordingly reason to ask what happens to ethnic differences in economic and social behavior when intelligence is held constant. This chapter examines that question.

The NLSY, with its large samples of blacks and Latinos (though not Asians), permits us to address the question directly and in detail. We will show what happens to the ethnic gap on a variety of indicators when IQ is taken into account. To anticipate: In some cases, large ethnic differences disappear altogether, or even reverse, with whites having the disadvantageous outcome compared to blacks and Latinos. In other cases, substantial differences remain, even after the groups are equated not only for cognitive ability but for parental SES and education as well. We do not try to press the analysis further, to find the other reasons why groups may differ socially. The goal of this chapter is to broaden the search for answers after three decades during which scholars have ignored the contribution of IQ to ethnic differences in the main social outcomes of everyday life.

First, we look at the indicators of success that were the focus of Part I, then the indicators of problems that were the focus of Part II.

ETHNIC DIFFERENCES IN EDUCATIONAL AND OCCUPATIONAL SUCCESS

We begin with what should be hailed as a great American success story. Ethnic differences in higher education, occupations, and wages are strikingly diminished after controlling for IQ. Often they vanish. In this sense, America has equalized these central indicators of social success.

Educational Attainment

The conventional view of ethnic differences in education holds that blacks and Latinos still lag far behind, based on comparisons of the percentage of minorities who finish high school, enter college, and earn college degrees. Consider, for example, graduation from high school. As of 1990, 84 percent of whites in the NLSY had gotten a high school diploma, compared to only 73 percent of blacks and 65 percent of Latinos, echoing national statistics.3 But these percentages are based on everybody, at all levels of intelligence. What were the odds that a black or Latino with an IQ of 103—the average IQ of all high school graduates—completed high school? The answer is that a youngster from either minority group had a higher probability of graduating from high school than a white, if all of them had IQs of 103: The odds were 93 percent and 91 percent for blacks and Latinos respectively, compared to 89 percent for whites.4

College has similarly opened up to blacks and Latinos. Once again, the raw differentials are large. In national statistics or in the NLSY sample, whites are more than twice as likely to earn college degrees than either blacks or Latinos.5 The average IQ of all college graduates was, however, about 114. What were the odds that a black or Latino with an IQ of 114 graduated from college? The figure below shows the answers.

All the graphics in this chapter follow the pattern of this one. The top three bars show the probabilities of a particular outcome—college graduation in this case—by ethnic group in the NLSY, given the average age of the sample, which was 29 as of the 1990 interview. In this figure, the top three bars show that a white adult had a 27 percent chance of holding a bachelor’s degree, compared to the lower odds for blacks (11 percent) and Latinos (10 percent). The probabilities were computed through a logistic regression analysis.

After controlling for IQ, the probability of graduating from college is about the same for whites and Latinos, higher for blacks

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The lower set of bars also presents the probabilities by ethnic group, but with one big difference: Now, the equation used to compute the probability assumes that each of these young adults has a certain IQ level. In this case, the computation assumes that everybody has the average IQ of all college graduates in the NLSY—a little over 114. We find that a 29-year-old (in 1990) with an IQ of 114 had a 50 percent chance of having graduated from college if white, 68 percent if black, and 49 percent if Latino« After taking IQ into account, blacks have a better record of earning college degrees than either whites or Latinos. We discuss this black advantage in Chapter 19, when we turn to the effects of affirmative action.

Occupational Status

One of the positive findings about ethnic differences has been that education pays off in occupational status for minorities roughly the same as it does for whites.6 This was reflected in the NLSY as well: Holding education constant, similar proportions of blacks, Latinos, and whites are found in the various occupational categories.7

To what extent does controlling for IQ produce the same result? We know from Chapter 2 that occupations draw from different segments of the cognitive ability distribution. Physicians come from the upper part of the distribution, unskilled laborers from the lower part, and so forth. If one ethnic group has a lower average IQ than another ethnic group, this will be reflected in their occupations, other things equal. What would the occupational distributions of different ethnic groups be after taking cognitive ability into account?

Sociologist Linda Gottfredson has examined this question for blacks and whites.8 If, for example, black and white males were recruited without discrimination into careers as physicians above a cutoff of an IQ of 112 (which she estimates is a fair approximation to the lower bound for the actual population of physicians), the difference in the qualifying population pools would place the black-white ratio at about .05—about one black doctor for every twenty white ones. According to census data, the actual per capita ratio of black to white male physicians was about .3 in 1980, which is about six black doctors for every twenty white ones. Another example is secondary school teaching, for which a similar calculation implies one black high school teacher for every ten white ones. The actual per capita ratio in 1980 was instead about six black teachers for every ten white ones. In both examples, there are about six times as many blacks in the occupation as there would be if selection by cognitive ability scores were strictly race blind. Gottfredson made these calculations for occupations spanning most of the range of skilled jobs, from physician and engineer at the top end to truck driver and meat cutter at the low end. She concluded that blacks are overrepresented in almost every occupation, but most of all for the high-status occupations like medicine, engineering, and teaching.9

We confirm Gottfredson’s conclusions with data from the NLSY by going back to the high-IQ occupations we discussed in Chapter 2: lawyers, physicians, dentists, engineers, college teachers, accountants, architects, chemists, computer scientists, mathematicians, natural scientists, and social scientists. Grouping all of these occupations together, what chance did whites, blacks, and Latinos in the NLSY have of entering them? The figure below shows the results.

Before controlling for IQ and using unrounded figures, whites were almost twice as likely to be in high-IQ occupations as blacks and more than half again as likely as Latinos.10 But after controlling for IQ, the picture reverses. The chance of entering a high-IQ occupation for a black with an IQ of 117 (which was the average IQ of all the people in these occupations in the NLSY sample) was over twice the proportion of whites with the same IQ. Latinos with an IQ of 117 had more than a 50 percent higher chance of entering a high-IQ occupation than whites with the same IQ.11 This phenomenon applies across a wide range of occupations, as discussed in more detail in Chapter 20.

After controlling for IQ, blacks and Latinos have substantially higher probabilities than whites of being in a high-IQ occupation

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Wages

We come now to what many people consider the true test of economic equality, dollar income. Two measures of income need to be separated because they speak to different issues. Wages provides a direct measure of how much a person gets per unit of time spent on the job. Annual family income reflects many other factors as well, being affected by marital status (does the family have two incomes?), nonwage income (from stock dividends to welfare), and the amount of time spent earning wages (did the person have a job for all fifty-two weeks of the year?). We begin with wages, the measure that most directly reflects the current workplace.

As of 1989, white year-round workers (of average age) in the NLSY sample (men and women) made an average of $6,378 more than blacks and $3,963 more than Latinos.12 The figure below shows what happens controlling for intelligence, this time presenting the results for a year-round worker with an IQ of 100. The average black who worked year-round was making less than 77 percent of the wage of the average employed white.13 After controlling for IQ, the average black made 98 percent of the white wage. For Latinos, the ratio after controlling for IQ was also 98 percent of the white wage. Another way to summarize the outcome is that 91 percent of the raw black-white differential in wages and 90 percent of the raw Latino-white differential disappear after controlling for IQ.

After controlling for IQ, ethnic wage differentials shrink from thousands to a few hundred dollars

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These results say that only minor earnings differences separate whites, blacks, and Latinos of equal IQ in the NLSY.14 Because this finding is so far from what the public commentary assumes, we explore it further. We focus on the situation facing blacks, because the black-white disparities have been at the center of the political debate. Parallel analyses for Latinos and whites generally showed smaller initial income disparities and similar patterns of convergence after controlling for IQ.

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

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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

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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

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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

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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

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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

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Children Living in Poverty

In 1992, 47 percent of black children under the age of 18 were living under the poverty line. This extraordinarily high figure was nearly as bad for Latino children, with 40 percent under the poverty line. For non-Latino whites, the proportion was about 14 percent.31 In approaching this issue through the NLSY, we concentrated on very young children, identifying those who had lived in families with incomes below the poverty line throughout their first three years of life. The results, before and after controlling for IQ, are shown in the upper figure on the next page. Given a mother with average IQ and average age, the probability that a black child in the NLSY lived in poverty throughout his first three years was only 14 percent, compared to an uncorrected black average of 54 percent. The reduction for Latinos, from 30 percent to 10 percent, was also large. The proportional difference between minorities and whites remains large.32

Controlling for IQ cuts the black-white disparity in low-birth-weight babies by half

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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.

The disparities in low HOME index scores between whites and minorities were large (see the lower figure on the next page). It was substantially reduced, by 52 percent for blacks and 64 percent for Latinos, but the black rate remained well over twice the white rate and the Latino rate close to twice the white rate.33

Controlling for IQ reduces the discrepancy between minority and white children living in poverty by more than 80 percent

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Controlling for IQ cuts the ethnic disparity in home environments by half for blacks and more than 60 percent for Latinos

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Indicators of the Child’s Development

Details on the several indexes of child development presented in Chapter 10 may be found in Appendix 6. We summarize them here by showing the proportion of children who showed up in the bottom decile of any of the indexes.

As the figure below shows, the ethnic disparities were not great even before controlling for IQ, and they more than disappeared after controlling for IQ. We leave this finding as it stands, but it obviously raises a number of issues. Since these indexes are based primarily on the mothers’ assessments, it is possible that women of different ethnic groups use different reference points (as has been found on ethnic differences in other self-report measures).34 It is also possible that the results may be taken at face value and that minority children with mothers of similar age and IQ do better on developmental measures than white children, which could have important implications. Filling out this story lies beyond the scope of our work, but we hope it will be taken up by others.35

Controlling for IQ more than eliminates overall ethnic differences in the developmental indexes

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Intellectual Development

We will discuss this topic in more detail in Chapter 15 as we present the effects of differential fertility across ethnic groups. The figure below shows the children of NLSY mothers who scored in the bottom decile on the Peabody Picture Vocabulary Test (PPVT) based on national norms, not the bottom decile of children within the NLSY sample. Controlling for the mother’s IQ reduces ethnic disparities considerably while once again leaving a broad gap with whites—in this case, roughly an equal gap between whites and both blacks and Latinos. The point that stands out, however, is the extremely large proportion of minority NLSY children who were in the bottom decile of the PPVT—in effect, meaning an IQ of 80 or lower—when national norms are applied. This is one of the reasons for concern about fertility that we discuss in Chapter 15.

Based on national norms, high percentages of minority children remain in the bottom decile of IQ after controlling for the mother’s IQ

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Crime

In the national data, blacks are about 3.8 times more likely to be arrested relative to their numbers in the general population than whites (Latino and non-Latino whites are combined in this comparison).36 Blacks are also disproportionately the victims of crime, especially violent crime. The ratio of black homicide victims to white as of 1990 was 7.7 to 1 for men and 4.8 to 1 for women.37

Sociologist Robert Gordon has analyzed black-white differences in crime and concluded that virtually all of the difference in the prevalence of black and white juvenile delinquents is explained by the IQ difference, independent of the effect of socioeconomic status.38 The only reliable indicator from the NLSY that lets us compare criminal behavior across ethnic groups is the percentage of young men who were ever interviewed while incarcerated.39 The figure below shows the standard comparison, before and after controlling for cognitive ability. Among white men, the proportion interviewed in a correctional facility after controlling for age was 2.4 percent; among black men, it was 13.1 percent. This large black-white difference was reduced by almost three-quarters when IQ was taken into account. The relationship of cognitive ability to criminal behavior among whites and blacks appears to be similar.40As in the case of other indicators, we are left with a nontrivial black-white difference even after controlling for IQ, but the magnitude of the difference shrinks dramatically.

Controlling for IQ cuts the black-white difference in incarceration by almost three-quarters

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The Middle Class Values Index

We concluded Part II with the Middle Class Values (MCV) Index, which scores a “yes” for those young adults in the NLSY who were still married to their first spouse, in the labor force if they were men, bearing their children within marriage if they were women, and staying out of jail, and scores a “no” for those who failed any of those criteria. Never-married people who met all the other criteria were excluded. The MCV Index, as unsophisticated as it is, has a serious purpose: It captures a set of behaviors that together typify (though obviously do not define) “solid citizens.” Having many such citizens is important for the creation of peaceful and prosperous communities. The figure below shows what happens when the MCV Index is applied to different ethnic groups, first adjusting only for age and then controlling for IQ as well. (In interpreting these data, bear in mind that large numbers of people of all ethnicities who did not score “yes” are leading virtuous and productive lives.) The ethnic disparities remain instructive. Before controlling for IQ, large disparities separate both Latinos and blacks from whites. But given average IQ, the Latino-white difference shrank to three percentage points. The difference between blacks and whites and Latinos remains substantial, though only about half as large as it was before controlling for IQ. This outcome is not surprising, given what we have already shown about ethnic differences on the indicators that go into the MCV Index, but it nonetheless points in a summary fashion to a continuing divergence between blacks and the rest of the American population in some basic social and economic behaviors.

The MCV Index, before and after controlling for IQ

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A MORE REALISTIC VIEW OF ETHNIC DISPARITIES IN SOCIAL AND ECONOMIC INDICATORS

If one of America’s goals is to rid itself of racism and institutional discrimination, then we should welcome the finding that a Latino and white of similar cognitive ability have the same chances of getting a bachelor’s degree and working in a white-collar job. A black with the same cognitive ability has an even higher chance than either the Latino or white of having those good things happen. A Latino, black, and white of similar cognitive ability earn annual wages within a few hundred dollars of one another.

Some ethnic differences are not washed away by controlling either for intelligence or for any other variables that we examined. We leave those remaining differences unexplained and look forward to learning from our colleagues where the explanations lie. We urge only that they explore those explanations after they have extracted the role—often the large role—that cognitive ability plays.

Similarly, the evidence presented here should give everyone who writes and talks about ethnic inequalities reason to avoid flamboyant rhetoric about ethnic oppression. Racial and ethnic differences in this country are seen in a new light when cognitive ability is added to the picture. Awareness of these relationships is an essential first step in trying to construct an equitable America.