The Bell Curve: Intelligence and Class Structure in American Life (119 page)

20
A high IQ is also worth extra income outside the high-IQ occupations as we defined them. The wages and salaries of people not in the high-IQ occupations but with an IQ in the top 10 percent earned over $11,000 more in 1989 (again in 1990 dollars) than those with IQs below the top decile. The median family income of those in the top IQ decile who did not enter the high-IQ professions was $49,000, putting them at the 72d percentile of family incomes.

21
Solon 1992; Zimmerman 1992. Women are not usually included in these studies because of the analytic complications arising in the recent dramatic changes in their work force participation. The correlation is even higher if the predictor of the son’s income is the family income rather than just the father’s (Solon 1992). These estimates of the correlation between father and son income represent a new finding. Until recently, specialists mostly agreed that income was not a strong family trait, certainly not like the family chin or the baldness that passes on from generation to generation, and not even as enduring as the family nest egg. They had concluded that the correlation between fathers and sons in income was between .1 and .2—very low. Expert opinion has, however, been changing. The older estimates of the correlation between fathers’ and sons’ incomes, it turns out, were plagued by two familiar problems that artificially depress correlation
coefficients. First, the populations used for gathering the estimates were unrepresentative. One large study, for example, used only high school graduates, which no doubt restricted the range of IQ scores (Sewell and Hauser 1975). Another problem has been measurement error—in the case of intergenerational comparisons of income, measurement error introduced by basing the analysis on a single year’s income. Averaging income over a few years reduces this source of error. Now, using the nationally representative, longitudinal data in the National Longitudinal Survey (NLS) and the Panel Study of Income Dynamics (PSID), economists have found the correlations of .4 to .5 reported in the text.

22
Solon 1992. For comparable estimates for Great Britain, see Atkinson, Maynard, and Trinder 1983.

23
U.S. Bureau of the Census 1991b, Table 32.

24
Herrnstein 1973, pp. 197-198.

25
For reviews of the literature as of 1980, see Bouchard 1981; Plomin and DeFries 1980. For more recent analyses, on which we base the upper bound estimate of 80 percent, see Bouchard et al. 1990; Pedersen et al. 1992.

26
Plomin and Loehlin 1989.

27
The proper statistical measure of variation is the standard deviation squared, which is called the variance.

28
Heritability is a concept in quantitative genetics; for a good textbook, see Falconer 1989.

29
Social scientists will recognize the heritability question as being akin to the general statistical model of variance analysis.

30
Plomin and Loehlin 1989.

31
Bouchard et al. 1990.

32
Estimating heritabilities from any relationship other than for identical twins is inherently more uncertain because the modeling is more complex, involving the estimation of additional sources of genetic variation, such as assortative mating (about which more below) and genetic dominance and epistasis. See Falconer 1989.

33
For a broad survey of all kinds of data published before 1981, set into several statistical models, the best fitting of which gave .51 as the estimate of IQ heritability, see Chipuer, Rovine, and Plomin 1990. Most of the data are from Western countries, but a recent analysis of Japanese data, based on a comparison of identical and fraternal twin correlations in IQ, yields a heritability estimate of .58 (Lynn and Hattori 1990).

34
The extraordinary discrepancy between what the experts say in their technical publications on this subject and what the media say the experts say is well described in Snyderman and Rothman 1988.

35
Cyphers et al. 1989; Pedersen et al. 1992.

36
Cyphers et al. 1989; Pedersen et al. 1992.

37
Based primarily on a large study of Swedish identical and fraternal twins followed into late adulthood (Pedersen et al. 1992).

38
Plomin and Bergeman 1987; Rowe and Plomin 1981.

39
IQ is not the only trait with a biological component that varies across socioeconomic strata. Height, head size, blood type, age at menarche, susceptibility to various congenital diseases, and so on are some of the other traits for which there is evidence of social class differences even in racially homogeneous societies (for review, see Mascie-Taylor 1990).

40
The standard deviation squared times the heritability gives variance due just to genes; the square root of that number is the standard deviation of IQ in a world of perfectly uniform environments:
= 11.6 A heritability of .4 would reduce the standard deviation from the normative value of 15 to 9.5; with a heritability of .8., it would be reduced to 13.4.

41
If we take the heritability of IQ to be .6, then the swing in IQ is 24 points for two children with identical genes, but growing up in circumstances that are at, say, the 10th and the 90th centile in their capacity to foster intelligence, a very large swing indeed. A less extreme swing from the 40th to the 60th centile in environmental conditions would move the average IQ only 4.75 points. In a normal distribution, the distance from the 10th to the 90th percentile is about 2.5 standard deviation units; from the 40th to the 60th percentile, it is about .5 standard deviation units. If the heritability is .8, instead of .6, then the swing from the 10th to the 90th percentile would be worth 17 IQ points, from the 40th to the 60th, 3.4 IQ points.

42
Burgess and Wallin 1943.

43
Spuhler 1968.

44
Jensen 1978. This estimate may be high for a variety of technical reasons that are still being explored, but apparently not a lot too high. For more, see DeFries et al. 1979; Mascie-Taylor 1989; Mascie-Taylor and Vandenberg 1988; Price and Vandenberg 1980; Watkins and Meredith 1981. In the 1980s, some researchers argued that data from Hawaii indicated a falling level of assortative mating for IQ, which they attributed to increased social mobility and greater access to higher education (Ahern, Johnson, and Cole 1983; Johnson, Ahern, and Cole 1980; Johnson, Nagoshi, and Ahern 1987). But the evidence seems to be limited to Hawaii. Other recent data from Norway and Virginia, not to mention the national census data developed by Mare and discussed in the text, fail to confirm the Hawaii data (Heath et al. 1985,1987). When intelligence and educational level are statistically pulled apart, the assortative mating for education, net of intelligence, is stronger than that for intelligence, net of educational level (Neale and McArdle 1990; Phillips et al. 1988).

45
For a discussion of regression to the mean, see Chapter 15. The calculation
in the text assumes a correlation of +.8 between the average child’s IQ and the midpoint of the parental IQs, consistent with a heritability of .6 and a family environment effect of .
2.
The estimate of average IQs in 1930 is explained in Chapter 1. The estimate for the class of 1964 (who were freshmen in 1960) is based on Harvard SAT-Verbal scores compared to the Educational Testing Service’s national norm study conducted in 1960, which indicates that the mean verbal score for entering Harvard freshmen was 2.9 SDs above the mean of all high school seniors—and, by implication, considerably higher than that for the entire 18-year old cohort (which includes the high school dropouts; Seibel 1962, Bender 1960). If we estimate the correlation between the SAT-Verbal and IQ as +.65 (from Donlon 1984), the estimated mean IQ of Harvard freshmen as of 1960 was about 130, from which the estimate of children’s IQ has been calculated.

46
With a parent-child correlation of .8, 64 percent of the variance is accounted for, 36 percent not accounted for. The square root of .36, which is .6, times 15, is the standard deviation of the distribution of IQ scores of the children of these parents. This gives a value of 9, from which the percentages in the text are estimated.

47
Operationally, Mare compared marriage among people with sixteen or more years of schooling with those who had fewer than sixteen years of schooling (Mare 1991, p. 23). For additional evidence of increasing educational homogamy in the 1970s and 1980s, see Qian and Preston 1993.

48
Oppenheimer, 1988.

49
DES 1992, Tables 160, 168.

50
Buss 1987. For evidence that this phenomenon is well underway, see Qian and Preston 1993.

51
In the NLSY, whose members graduated from high school in the period 1976-1983, 59.3 percent had obtained a bachelor’s or higher degree by 1990. In the “High School and Beyond” study conducted by the Department of Education, only 44 percent of 1980 high school graduates who were in the top quartile of ability had obtained a B.A. or B.S. by 1986 (Eagle 1988a, Table 3).

52
See Chapter 1.

53
Authors’ analysis of the NLSY.

54
Authors’ analysis of the NLSY.

55
SAUS 1991, Table 17.

1
Sussman and Steinmetz 1987. This is still a valuable source of information about myriad aspects of family life, mainly in America.

2
For example, in the last ten years, out of hundreds of articles and research notes, the preeminent economics journal,
American Economic Review,
has published just a handful of articles that call upon IQ as a way of understanding such problems. The most conspicuous exceptions are Bishop 1989; Boissiere et al. 1985; Levin 1989; Silberberg 1985; Smith 1984.

3
The criterion for eligibility was that they be ages 14 to 21 on January 1, 1979, which meant that some of them had turned 22 by the time the first interview occurred.

4
Details of the Department of Defense enlistment tests, the ASVAB, are also given in Appendix 3.

5
The test battery was administered to small groups by trained test personnel. That each NLSY subject was paid $50 to take the test helped ensure a positive attitude toward the experience.

6
See Appendix 3 for more on the test and its
g
loading, and the Introduction for a discussion of
g
itself.

7
Raw AFQT scores in the NLSY sample rose with age throughout the age cohorts who were still in their teens when they took the test. The simplest explanation is that the AFQT was designed by the military for a population of recruits who would be taking the test in their late teens, and younger youths in the NLSY sample got lower scores for the same reason that high school freshmen get lower SAT scores than high school seniors. However, a cohort effect could also be at work, whereby (because of educational or broad environmental reasons) youths born in the first half of the 1960s had lower realized cognitive ability than youths born in the last half of the 1950s. There is no empirical way of telling which reason explains the age-related differences in the AFQT or what the mix of reasons might be. This uncertainty is readily handled in the multivariate analyses by entering the subject’s birthdate as an independent variable (all the NLSY sample took the AFQT within a few months of each other in late 1980). When we present descriptive statistics, we use age-equated centiles.

8
We assigned the NLSY youths to a cognitive class on the basis of their age-equated centile scores. We use the class divisions as a way to communicate the data in an easily understood form. It should be remembered, however, that all of the statistical analyses are based on the actual test scores of each individual in the NLSY.

9
Regression analysis is only remotely related to the regression to the mean referred to earlier. See Appendix 1.

10
Age, too, is always part of the analytic package, a necessity given the nature of the NLSY sample (see note 7).

11
The white sample for the NLSY was chosen by first selecting all who were categorized by the interview screener as nonblack and non-Hispanic. From
this group, we excluded all youths who identified their own ethnicity as Asian, Pacific, American Indian, African, or Hispanic.

1
Ross et al. 1987. The authors used the sample tapes for the 1940 and 1950 census to calculate the figures for 1939 and 1949, antedating the beginning of the annual poverty statistics in 1959. The numbers represent total money income, including government transfers. The figure for 1939 is extrapolated, since the 1939 census did not include data on income other than earnings. It assumes that the ratio of poverty based on earnings to poverty based on total income in 1949 (.761) also applied in 1939, when 68.1 percent of the population had earnings that put them below the poverty line. Since government transfers increased somewhat in the intervening decade, the resulting figure for 1939 should be considered a lower bound.