Reinhard_Heini
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Most people are aware that there are significant disparities between blacks and whites in the United States with regard to a wide range of important social outcomes, including crime, income, education, poverty, welfare usage, etc. For almost every measurable metric of important life outcomes, blacks perform significantly worse than whites. In this post, I will cite studies showing that many of these disparities are likely caused by the significant cognitive differences between blacks and whites. I begin by illustrating a few examples of the disparities between blacks and whites with respect to important life outcomes. Then I briefly review evidence demonstrating the predictive validity and causal influence of cognitive ability for these outcomes. Next, I present data illustrating the scope and magnitude of the black-white cognitive ability gap. Finally, I provide evidence indicating that many of the aforementioned disparities between blacks and whites are (mostly) eliminated after controlling for youth cognitive ability.
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The same data shows that black households were over twice as likely to be poor as white households in the same year (21.2% vs 8.7%, Table 3). More recent data [archived] from the US census shows that, while the black poverty rate has decreased significantly since the 1960s, there are still large disparities in poverty rate between blacks and whites today:
Part of the explanation for racial disparities in household income is that black households are far less likely to be dual-income households than white households, independently of any income disparity between black and white individuals. However, data [archived] from the National Center for Education Statistics shows black workers have far lower annual earnings than white workers. The median annual earnings for black workers was $11,200 lower than the median earnings for white workers ($33,700 vs $44,900):
Controlling for educational attainment does not eliminate the disparity, as black workers have lower median earnings than white workers at each of the major levels of education:
Data from the Pew Research Center [archived] also showed significant racial disparities in wealth that have persisted for generations. In fact, the ratio of median white wealth to median black wealth is greater today than it was in the 1980s:
At every range of parental income, black children are far less likely to exceed their parent’s income:
I wrote more on racial disparities in intergenerational mobility in this post.
Data from Pew Research Center [archived] shows that the black-white disparity in high school completion has narrowed significantly in recent decades, although large gaps remain. On the other hand, the college completion gap between blacks and whites has barely changed within 50 years.
In 2003, the Bureau of Justice Statistics [archived] (Figure 4) released a report showing that 1 in 3 black males could be expected to go to prison if the current rates of imprisonment had remained unchanged.
These disparities show that, given 2003 rates of incarceration, black females were about as likely to be incarcerated as white males. Fortunately, incarceration rates have decreased since then, so the lifetime chances of being incarcerated have lowered since then as well. Recent data from the Bureau of Justice Statistics (2020) [archived] shows that blacks are much more likely to be incarcerated than whites, although the disparity has decreased in recent years (Figure 1). The racial disparities are greatest for the youngest males. In fact, the imprisonment rate for black males aged 18-19 years is over 12 times higher than the rate for similarly aged white males (Figure 2).
Disparities in troublesome behavior between blacks and whites appear far before adulthood. For example, among middle-schoolers [archived], black males are suspended at 3 times the rate for white males, and black females are suspended at over 4 times the rate for white females. Furthermore, despite making up just 18% of enrolled preschoolers, black children account for 48% [archived] of preschool children suspended more than once.
I go into more detail on the racial disparities in crime and misconduct in a separate post.
This section will summarize points that I’ve made about the predictive validity of cognitive ability in a separate post.
My working definition of cognitive ability is measured by IQ tests fairly accurately. It is important to understand IQ because, as Nisbett et al. (2012) [archived] notes, IQ is the measure of intelligence for which “the bulk of evidence pertinent to intelligence exists” (page 131). To start, one should understand how IQ scores are distributed. IQ scores are normed for a given population to produce a mean score of 100 and a standard deviation (SD) of 15 points. Because IQ scores are normally distributed, 32% of the population has an IQ score of more than a standard deviation away from the mean. In other words, about 68% of the population has scores between 85 and 115. About 5% of the population has an IQ score of more than two standard deviations (30 points) from the mean. In other words, about 95% of the population has scores between 70 and 130 (Neisser et al. (1996) [archived], page 78).
My working definition of cognitive ability is also measured fairly accurately by other tests that are not officially IQ tests. This is because there are many tests that are highly g-loaded even though they aren’t officially IQ tests. Highly g-loaded tests produce test results that are strong measures of g, the general factor of intelligence at the top of the hierarchy in the CHC theory of cognitive abilities. g-loaded tests are important because, as Gottfredson (2002) [archived] notes, the more g-loaded a test is, “the better it predicts performance, including school performance, job performance, and income” (page 28). She also states the following regarding g (page 27):
Rindermann, Becker, and Coyle (2020) [doi] surveyed the opinions of over 100 experts in the field of intelligence about a variety of questions. One of the questions in the survey was “to what degree is the average socioeconomic status (SES) in Western societies determined by his or her IQ?” The survey found that “Experts believed 45% of SES variance was explained by intelligence and 55% by non-IQ factors (Table 3). 51% of experts believed that the contribution of intelligence (to SES) was below 50%, 38% above 50%, and 12% had a 50–50 opinion.” That is, experts believe that roughly half of the variance in socioeconomic status in Western societies is due to intelligence.
The analysis concludes with the following (page 415):
These findings on the IQ-income correlations were corroborated by Zagorsky (2007) [archived]. He also used the National Longitudinal Survey of Youth 1979 to examine the association between youth IQ and income and net worth measured between the ages of 33 and 41 (page 491). The benefit of this study over the previous data is that this study was able to report on outcomes at a later stages in life. The study reported medium-large correlations between IQ and income (r = 0.30) and small-medium correlations between IQ and net worth (r = .16) (Table 2). The median incomes and net worth at different IQ points were as follows:
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Racial Inequalities
Income
Black households have far lower average incomes than white households. US census data (2017) [archived] shows that the average black household income was more than one-third lower than the average white household income in 2017 ($40,258 vs $68,145, Table 1). This disparity has barely budged within over 50 years:
The same data shows that black households were over twice as likely to be poor as white households in the same year (21.2% vs 8.7%, Table 3). More recent data [archived] from the US census shows that, while the black poverty rate has decreased significantly since the 1960s, there are still large disparities in poverty rate between blacks and whites today:
Part of the explanation for racial disparities in household income is that black households are far less likely to be dual-income households than white households, independently of any income disparity between black and white individuals. However, data [archived] from the National Center for Education Statistics shows black workers have far lower annual earnings than white workers. The median annual earnings for black workers was $11,200 lower than the median earnings for white workers ($33,700 vs $44,900):
Controlling for educational attainment does not eliminate the disparity, as black workers have lower median earnings than white workers at each of the major levels of education:
Data from the Pew Research Center [archived] also showed significant racial disparities in wealth that have persisted for generations. In fact, the ratio of median white wealth to median black wealth is greater today than it was in the 1980s:
Income mobility
A report by Mazumder (2008) [archived] published by Pew Charitable Trusts used the NLSY79 to examine factors relevant to income mobility. Income mobility was examined by investigating family income in adolescence (1978-1980) and family income as adults (1997-2003). Prior to controlling for any covariates, the study finds stark racial differences in income mobility. For example, about 75% of whites raised in the bottom income quintile eventually transition out of that quintile, whereas only 56% of blacks do the same. In fact, blacks raised in the 2nd highest income quintile are equally as likely to end in the bottom quintile as are whites raised in the lowest income quintile (24.6% vs 24.9%):
At every range of parental income, black children are far less likely to exceed their parent’s income:
I wrote more on racial disparities in intergenerational mobility in this post.
Education
More data from the National Center for Education Statistics (NCES)[archived] shows large disparities in educational attainment between blacks and whites. For example, blacks are about twice as likely as whites to fail to complete High School (Figure 27.1) and they are about half as likely to attain a bachelor’s degree (Figure 27.3).Data from Pew Research Center [archived] shows that the black-white disparity in high school completion has narrowed significantly in recent decades, although large gaps remain. On the other hand, the college completion gap between blacks and whites has barely changed within 50 years.
Crime and misbehavior
Black people are disproportionately involved in criminality. Data from FBI crime statistics (2015) [archived] shows that despite making up only 13% of the US population, black people commit 36% of violent crime in the US. Even worse, they commit over half of the robberies and murders in the country. Among criminals under the age of 18, black youth commit over 60% of the robberies and murders in the country, and over half of the violent crime.In 2003, the Bureau of Justice Statistics [archived] (Figure 4) released a report showing that 1 in 3 black males could be expected to go to prison if the current rates of imprisonment had remained unchanged.
These disparities show that, given 2003 rates of incarceration, black females were about as likely to be incarcerated as white males. Fortunately, incarceration rates have decreased since then, so the lifetime chances of being incarcerated have lowered since then as well. Recent data from the Bureau of Justice Statistics (2020) [archived] shows that blacks are much more likely to be incarcerated than whites, although the disparity has decreased in recent years (Figure 1). The racial disparities are greatest for the youngest males. In fact, the imprisonment rate for black males aged 18-19 years is over 12 times higher than the rate for similarly aged white males (Figure 2).
Some people might object that these statistics only show that black people are more likely to be arrested or incarcerated without showing that they black people are more likely to commit crimes. A simple test of this hypothesis involves looking at the leading causes of death by race. If black people are much more likely to be killed via homicide, then that is evidence that black people are far more likely to commit homicide (since the vast majority of homicides are intraracial rather than interracial). The CDC (2015) [archived] reports that homicide is the leading cause of death for black males aged 15-34, with nearly half of deaths for men aged 15-24 the result of homicide (see page 34). Contrast this with white males of the same age for whom homicide causes roughly between 3-5% of deaths (see page 27). In fact, the death rate due to homicides for blacks aged 20-24 (110.8 deaths per 100,000 population) is over 20 times the rate for similarly aged whites (5.4 deaths per 100,000 population).Disparities in troublesome behavior between blacks and whites appear far before adulthood. For example, among middle-schoolers [archived], black males are suspended at 3 times the rate for white males, and black females are suspended at over 4 times the rate for white females. Furthermore, despite making up just 18% of enrolled preschoolers, black children account for 48% [archived] of preschool children suspended more than once.
I go into more detail on the racial disparities in crime and misconduct in a separate post.
Why cognitive ability matters
This section will summarize points that I’ve made about the predictive validity of cognitive ability in a separate post.
Definitions
When I say “cognitive ability”, I’m referring to the definition of “intelligence” given by Gottfredson (1997) [archived]:For a more formal definition of the meaning of cognitive ability that I have in mind, see the Cattell–Horn–Carroll (CHC) theory of human cognitive abilities, which has been deemed the “most widely accepted theory” of intelligence (Sternberg 2012). The CHC theory is a synthesis of the Cattell–Horn Gf–Gc and Carroll Three-Stratum models, which have “have emerged as the consensus psychometric-based models for understanding the structure of human intelligence” (McGrew 2009). The CHC theory affirms that there are three strata of intelligence that hierarchically relate to one another. At the top of the hierarchy (stratum III) is the general factor of intelligence (also referred to as the g factor or g), which will be explained more later in this post. In the middle of the hierarchy (stratum II) are broad abilities such as fluid and crystalized intelligence. At the bottom of the hierarchy (stratum I) are narrow abilities nested under each broad ability. The broad abilities are comprehension-knowledge (Gc), fluid reasoning (Gf), quantitative knowledge (Gq), reading & writing ability (Grw), short-term memory (Gsm), long-term storage and retrieval (Glr), visual processing (Gv), auditory processing (Ga), and processing speed (Gs). The degree to which a test measures these abilities corresponds to the degree to which the test measures my definition of cognitive ability. Fortunately, virtually all tests of mental abilities measure at least some of these abilities, and all tests measure g to some extent.
My working definition of cognitive ability is measured by IQ tests fairly accurately. It is important to understand IQ because, as Nisbett et al. (2012) [archived] notes, IQ is the measure of intelligence for which “the bulk of evidence pertinent to intelligence exists” (page 131). To start, one should understand how IQ scores are distributed. IQ scores are normed for a given population to produce a mean score of 100 and a standard deviation (SD) of 15 points. Because IQ scores are normally distributed, 32% of the population has an IQ score of more than a standard deviation away from the mean. In other words, about 68% of the population has scores between 85 and 115. About 5% of the population has an IQ score of more than two standard deviations (30 points) from the mean. In other words, about 95% of the population has scores between 70 and 130 (Neisser et al. (1996) [archived], page 78).
My working definition of cognitive ability is also measured fairly accurately by other tests that are not officially IQ tests. This is because there are many tests that are highly g-loaded even though they aren’t officially IQ tests. Highly g-loaded tests produce test results that are strong measures of g, the general factor of intelligence at the top of the hierarchy in the CHC theory of cognitive abilities. g-loaded tests are important because, as Gottfredson (2002) [archived] notes, the more g-loaded a test is, “the better it predicts performance, including school performance, job performance, and income” (page 28). She also states the following regarding g (page 27):
Furthermore, g scores extracted from different test batteries correlate nearly perfectly with one another (Johnson et al. 2004, Johnson et al. 2008, Kaufman et al. 2012). That being said, we can rely on tests that are not official IQ tests as good measures of cognitive ability if they are highly g-loaded. For example, ACT tests, SAT tests, AFQT tests, and even vocabulary tests are highly g-loaded, which make them satisfactory measures of cognitive ability on my working definition.
Expert consensus
The expert consensus is that cognitive ability (as defined earlier) is a very powerful predictor, often the most powerful predictor, of a number of important social outcomes. For example, in a recent review of intelligence research by experts in the field, Nisbett et al. (2012) [archived] summarized the predictive power of IQ as follows (page 131):Gottfredson (1997) [archived] was a very brief 3-page statement that outlines conclusions regarded as mainstream by over 50 experts in intelligence and allied fields. Some of the conclusions they reached regarding the causal influence of cognitive ability were as follows (page 14):
- IQ is strongly related, probably more so than any other single measurable human trait, to many important educational, occupational, economic, and social outcomes. Its relation to the welfare and performance of individuals is very strong in some arenas in life (education, military training), moderate but robust in others (social competence), and modest but consistent in others (law-abidingness). Whatever IQ tests measure, it is of great practical and social importance.
- A high IQ is an advantage in life because virtually all activities require some reasoning and decision-making. Conversely, a low IQ is often a disadvantage, especially in disorganized environments. Of course, a high IQ no more guarantees success than a low IQ guarantees failure in life. There are many exceptions, but the odds for success in our society greatly favor individuals with higher IQs.
- The practical advantages of having a higher IQ increase as life settings become more complex (novel, ambiguous, changing, unpredictable, or multifaceted). For example, a high IQ is generally necessary to perform well in highly complex or fluid jobs (the professions, management); it is a considerable advantage in moderately complex jobs (crafts, clerical and police work); but it provides less advantage in settings that require only routine decision making or simple problem solving (unskilled work)
- Differences in intelligence certainly are not the only factor affecting performance in education, training, and highly complex jobs (no one claims they are), but intelligence is often the most important. When individuals have already been selected for high (or low) intelligence and so do not differ as much in IQ, as in graduate school (or special education), other influences on performance loom larger in comparison.
Rindermann, Becker, and Coyle (2020) [doi] surveyed the opinions of over 100 experts in the field of intelligence about a variety of questions. One of the questions in the survey was “to what degree is the average socioeconomic status (SES) in Western societies determined by his or her IQ?” The survey found that “Experts believed 45% of SES variance was explained by intelligence and 55% by non-IQ factors (Table 3). 51% of experts believed that the contribution of intelligence (to SES) was below 50%, 38% above 50%, and 12% had a 50–50 opinion.” That is, experts believe that roughly half of the variance in socioeconomic status in Western societies is due to intelligence.
Predictive validity
A meta-analysis by Strenze (2007) [archived] shows that intelligence (measured by IQ scores) is a great predictor of future socioeconomic success. Socioeconomic success was measured as educational level, occupational status, and income. The analysis found that IQ measured before age 19 was a powerful predictor of socioeconomic success after age 29 (see “best studies” on Table 1).
The analysis concludes with the following (page 415):
For more concrete examples of the association between adolescent cognitive ability and socioeconomic outcomes, see Murray (1998) [archived]. In this work, Murray used data from the NLSY79 to measure the predictive power of cognitive ability on a variety of socioeconomic outcomes. He separated subjects from the NLSY79 into 5 different “cognitive classes”: those who scored in the 90th+ AFQT percentile (classified as “very bright”), those who scored in the 75th-89th AFQT percentile (“bright”), those who scored in the 25th-75th AFQT percentile (“normal”), those who scored in the 10th-24th AFQT percentile (“dull”), and those who scored below the 10th percentile (“very dull”). He then reported the average levels of socioeconomic success for each cognitive class. As expected, those from the higher cognitive classes attained far higher levels of success than those in the lower cognitive classes. Consider the following findings (taken from tables 6-1 through 6-3):
| Cognitive Class (percentile range) | Mean Years of Education (1994) | Percentage obtaining a B.A. (1994) | Mean Weeks Worked (1993) | Median Earned Income (1993) |
| Very Bright (90th+) | 16.5 | 77% | 45.4 | $36,000 |
| Bright (75th – 89th) | 15.0 | 50% | 45.2 | $27,000 |
| Normal (25th – 74th) | 13.2 | 16% | 41.8 | $21,000 |
| Dull (10th – 24th) | 11.9 | 3% | 36.5 | $13,000 |
| Very Dull (10th-) | 10.9 | 1% | 30.7 | $7,500 |
| IQ test score | Median income (2021 dollars) | Median net worth (2021 dollars) |
| 120 | $48,681 ($78,587) | $127,500 ($184,875) |
| 110 | $40,884 ($59,282) | $71,445 ($103,595) |
| 100 | $36,826 ($53,398) | $57,550 ($83,448) |
| 90 | $30,881 ($44,777) | $37,500 ($54,375) |
| 80 | $18,467 ($26,777) | $10,500 ($15,225) |
| Overall | $35,918 ($52,081) | $55,250 ($80,112) |
- The raw values are the figures in 2004 dollars, taken directly from the study. The values in parenthesis are in 2021 dollars, by multiplying the raw values by 1.45.
