MARCO TEÓRICO
3. Participación ciudadana en la política pública. Expectativas de satisfacción de necesidades necesidades
3.1 Expectativas de la política pública-satisfacción de necesidades
2. High IQs and High Earnings
3. Economists’ Studies of Effects of IQ on Earnings 4. Intelligence and Educational Attainment
5. Intelligence and Socioeconomic Status 6. Intelligence and Trainability
7. Intelligence and Job Proficiency
I
n this chapter we review the evidence showing that intelligence is a determinant of earnings among individuals. This is the foundation of our thesis that the intelligence of national populations is a major determinant of national per capita incomes and rates of economic growth.
We also review the evidence showing that intelligence is a determinant of trainability and job proficiency which explains why those at higher levels of intelligence are able to secure higher earnings.
1. Effects of Intelligence on Earnings
Because we are concerned with the relationship between IQs and earnings among nations, it is important to begin by establishing that intelligence is a determinant of earnings among individuals. There have been a number of studies showing that this is so. Some of these studies have measured intelligence in childhood or adolescence and related
these to earnings in adulthood, while others have measured intelligence in adulthood at the same time as earnings. Several studies have shown that intelligence assessed in childhood from the age of about 8 years and above is fairly stable over the life span and is correlated at about 0.7 to 0.8 with intelligence in adulthood (McCall, 1977; Li, 1975).
The longest span of time over which a high stability of IQ has been demonstrated is 66 years. This was shown in a study by Deary et al.
(2000) in which children intelligence tested in 1932 at the age of eleven were tested again in 1998 at the age of 77. The correlation between the two scores was 0.77. It does not therefore make much difference for studies of the relation between intelligence and earnings whether IQs are assessed in childhood or adolescence and shown to predict future earnings, or whether IQs and earnings are assessed simultaneously among adults. Since intelligence is fairly stable from around the age of eight, both methodologies imply that intelligence predicts earnings obtained in adulthood.
The results of the major studies of the relationship between intelli
gence and earnings are summarized in Table 3.1. Row 1 to 4 gives data from the Netherlands for a sample whose IQs were tested at the age of 12 years and whose earnings were obtained at the ages of 43 and 53.
Rows 1 and 2 give results for men and show that IQs were correlated at 0.17 with earnings at age 43 and 0.19 with earnings at age 53. Rows 3 and 4 give the corresponding data for women and show that IQs were correlated at 0.03 with earnings at age 43 and 0.19 (the same as men) with earnings at age 53. Probably the low correlation between IQ and earnings for women at age 43 is because many women were rearing children and had little or no earnings, but by the age of 53 the women had resumed work and the correlation between IQ and earnings become exactly the same as for men. Row 5 gives data from Norway for a sample whose IQs were tested at age 18 years and whose IQs were cor
related at 0.33 with earnings ascertained subsequently (age not given).
Rows 6 through 13 give data from Sweden for a sample born in 1928 in Malmo and intelligence tested at the age of 10 years and again at the age of 20 years while doing military service. Earnings were ascertained at the ages of 25,30,35, and 43. Rows 6 through 9 give the correlations between IQs at age 10 and adult earnings and show that these were negligible (0.08) at the age of 20 but become statistically significant and increasingly large from the age of 25 until they reach 0.40 at the age of 34 IQ and Global Inequality
43. Rows 10 through 13 give the corresponding correlations between IQs at age 20 and adult earnings and show the same trend with the cor
relation reaching 0.50 at the age of 43. The correlations between IQs and earnings are higher when IQs are measured at the age of 20 than at age 10, probably because the IQs at age 20 are more vahd.
Rows 14 through 29 give data for the relationship between intelli
gence and earnings in the United States. Row 14 gives the results of the first study by Duncan (1968) who presented data from the 1964 Current Population Survey carried out by the National Opinion Research Center (NORC) on a sample of white males with an average age of 30 (range 24-35). Their IQs were obtained from the AFQT (Armed Forces Qualification Test) taken from their military records and showed that their IQ was correlated at 0.31 with their earnings (the size of the sample is not given). Rows 15 through 18 give data for a sample from New England. The age at which the IQs were obtained is not given. The correlation between the IQs and earnings at the age of 19 was 0.15 and increased progressively as the sample grew older up to 0.49 at the age of 34. This confirms the results obtained by Fagerhnd (1975) in Sweden showing that the correlation between the IQs and earnings increases with age. Row 19 gives a correlation of 0.26 between the IQs of a sample in Wisconsin and earnings at the age of 25.
Rows 20 through 23 (Brown and Reynolds, 1975) are derived from a study of the relation between the IQ of males measured in early adulthood and earnings approximately 12 years later for samples of 24,819 whites and 4,008 blacks. The correlations of IQ and earnings are 0.24 and 0.33 for whites at the approximate ages of 30 and 36, and 0.08 and 0.13 for blacks at the same ages. The explanation for the lower correlations for blacks is not clear. Row 24 (Murray, 1998) is derived from the National Longitudinal Study of Youth, a nationally representative American sample of 12,686 males intelligence tested in 1980 between the ages of 14 and 23 and whose incomes were recorded in 1992 at the average age of 30; the correlation between IQ and income is 0.37. Row 25 gives data for 1943 sibling pairs from the NLSY sample and shows a correlation between IQ and income of 0.35. The point of using pairs of siblings is that it is possible to estimate the heritability of income, calculated in this study at 0.42. Row 26 gives the highest correlation (0.53) in the table between IQ at age 12 and income at the age of 45.
Intelligence as a Déterminent o f Earnings and Achievement 35
Rows 27 and 28 (Nyborg and Jensen, 2001) give data obtained from samples of white and black men who had served in the United States Armed Forces in the Vietnam war, of whom 62% were draftees Table 3.1. Correlations between IQ and earnings
36 IQ and Global Inequality
Country Number Sex Age Age r Reference
1 Netherlands 835 M 12 43 0.17 Dronkers, 1999
2 Netherlands 819 M 12 53 0.19 Dronkers, 1999
3 Netherlands 350 F 12 43 0.03 Dronkers, 1999
4 Netherlands 237 F 12 53 0.19 Dronkers, 1999
5 Norway 1,082 M/F 18 - 0.33 Tambs et al., 1989
6 Sweden 346 M 10 25 0.08 Fagerlind, 1975
7 Sweden 460 M 10 30 0.22 Fagerlind, 1975
8 Sweden 631 M 10 35 0.34 Fagerlind, 1975
9 Sweden 707 M 10 43 0.40 Fagerlind, 1975
10 Sweden 312 M 20 25 0.10 Fagerlind, 1975
11 Sweden 410 M 20 30 0.22 Fagerlind, 1975
12 Sweden 532 M 20 35 0.43 Fagerlind, 1975
13 Sweden 585 M 20 43 0.50 Fagerlind, 1975
14 USA - M 18 30 0.31 Duncan, 1968
15 USA 345 M - 19 0.15 Hause, 1971
16 USA 345 M - 24 0.29 Hause, 1971
17 USA 345 M - 29 0.45 Hause, 1971
18 USA 345 M - 34 0.49 Hause, 1971
19 USA 4,388 M 17 25 0.26 Hauser et al., 1973
20 USA-whites 24,812 M 18 30 0.24 Brown & Reynolds, 1975 21 USA-whites 24,812 M 18 36 0.33 Brown & Reynolds, 1975 22 USA-blacks 4,008 M 18 30 0.08 Brown & Reynolds, 1975 23 USA-blacks 4,008 M 18 36 0.13 Brown & Reynolds, 1975
24 USA 12,686 M/F 18 30 0.37 Murray, 1998
25 USA 1,943 M/F 18 30 0.35 Rowe et al., 1998
26 USA - M 12 45 0.53 Judge et al., 1999
27 USA-whites 3,484 M 19 37 0.36 Nyborg & Jensen, 2001 28 USA-blacks 493 M 19 37 0.37 Nyborg & Jensen, 2001
29 USA 1,448 M 17 27 0.22 Murnane et al., 2001
and 38% were enlisted. Their IQs were obtained in 1967 at the age of 19 and their earnings were obtained at the age of approximately 37. In this sample the correlations between IQs and earnings were virtually identical for whites (0.36) and blacks (0.37), unlike the results in rows 18 and 19 where the correlations are greater for whites. These correlations will be a little lower than would be obtained for a fully representative sample of the population because those with IQs below the tenth percentile are not accepted into the armed services. The final row gives a correlation of 0.22 between IQs at the age of 17 and income at the age of 27.
Looking at the results as a whole, it is apparent that all of them show positive correlations between IQs obtained in childhood or adolescence and earnings in adulthood. These studies show that IQ is a determinant of income because IQs are established quite early in childhood and predict income achieved in adulthood (e.g., Duncan, 1968; Duncan, Featherman, and Duncan, 1972; Jencks, 1972; McCall, 1977; Jensen, 1998). It might be supposed that the family environment is the common cause of children’s intelligence and their subsequent adult earnings, but this is improbable because it has been shown by Duncan, Featherman, and Duncan (1972) and by Jencks (1972) that the positive relation between childhood IQ and adult income is present when parental socioeconomic status is controlled. Furthermore, among pairs of brothers who have been raised in the same family and have experienced the same environment, the brother with the higher IQ in childhood has the greater earnings in adulthood (Jencks,1972; Murray,
1998; Waller, 1971),
The median correlation between IQ and earnings at the age of the thirties and forties is 0.36. The effect of a correlation of 0.36 between intelligence and earnings is to produce substantial differ
ences in the earnings of high and low IQ groups. As Jencks (1972, p. 222) noted, men inducted in the Korean War who had been tested and scored above the 80th percentile for intelligence, representing IQs of 110 and over, had personal incomes when they returned to civilian life 34 percent above the national average. Conversely, the military inductees who scored below the 20th percentile on intel
ligence, representing IQs of below 90, had personal incomes when they returned to civilian life approximately 34 percent below the national average.
It will be noted that the results set out in Table 3.1 show that the Intelligence as a Déterminent of Earnings and Achievement 37
correlations between IQ and earnings are quite low in early adulthood but become larger among older age groups in their thirties and forties.
In Fagerlind’s (1975) Swedish data IQ and earnings are correlated at only 0.08 among 25-year-olds but at 0.40 among 43-year-olds.
Similarly, in Hause’s American data IQ and earnings are correlated at only 0.15 among 19-year-olds but at 0.49 among 34-year-olds. This age effect has been usefully illustrated by Murray (1997) for the National Longitudinal Study of Youth sample. He divides the sample into five IQ groups from 65-75 up to 125+ and gives their average earnings at the ages of 18, 26, and 32 years. His results are shown in Table 3.2.
At the age of 18, the middle IQ group (IQs 90-109) have the highest average earnings ($8,000), while the earnings of the highest IQ group (IQs 125+) are quite low ($3,000). By the age of 26, the earnings of the groups have become sorted by IQ but the highest IQ group earns only marginally more ($21,000),than the next highest IQ group ($20,000).
By the age of 32, the differences in the earnings of the groups have become greater, with the highest IQ group earning substantially more ($36,000) than the next highest IQ group ($27,000), and some seven times more than the lowest IQ group ($5,000). There are two major explanations for these differences. First, in late adolescence and early adulthood, most of the high IQ groups are at school or in college so they do not earn as much as the middle IQ group who are mainly working.
Second, the earnings of all the groups increase as they get older, but the earnings of the higher IQ groups increase more than those of the lower IQ groups. The reason for this is that everyone acquires skills as they get older, but the higher IQ groups acquire more skills than the lower IQ groups because intelligent people can learn skills that less intelligent people are unable to learn.
Table 3.2. Relation bettveen IQ and earnings (US dollars) at ages 18, 26, and 32
38 IQ and Global Inequality
125+ 110-124 90-109 75-89 60-75
18 3,000 8,000 8,000 5,000 2,000
26 21,000 20,000 16,000 10,000 3,000
32 36,000 27,000 20,000 12,400 5,000