First, I shall review the important news from this year’s SAT and ACT score reports. I used the ACT-to-SAT conversion equation that I extracted from the conversion table to construct a summary graph of overall ACT-SAT scores for each race and gender. Asian scores continued to rise, despite the College Board’s South Korean crackdown, which was based upon suspicions of widespread cheating. Meanwhile, overall scores fell, and whites, Native Americans, and men declined this year more than any of the previous sixteen available years.
Native Americans now barely score higher than Hispanic Americans. Native-American ACT scores slipped especially fast, and their average score on the optional ACT writing exam now equals those of African Americans. Since many white people have Native-American ancestry, and Canadian and US Native Americans tend to have high amounts of European ancestry, Native-American score trends could reflect changing cultural attitudes about racial identification, but their absolute number of test participants has not changed greatly.
I previously commented on evidence for possible white decline. So far, the evidence is subtle. If future scores demonstrate long-term decline, it could signify the “dumbing down” of education or culture, dysgenics, minority-centered education reforms, or low rates of whites taking test preparation services.
Because Asian score increases have been steady and measured, I believe that these represent genuine progress, even with or perhaps due to the same root causes as the reported cheating scandals among Asians. However, I suspect that Asian progress will eventually level off because most racial score gaps have stayed remarkably constant, and I think nature influences testing potential, especially among those of adequate means.
SAT annual reports provide scores of students grouped by their parents’ income and education levels. These graphs of that data should not surprise anyone.
The fluctuation of income categories tells an interesting story about the past two decades. The number of people with six-figure incomes took off not that long ago.
Despite the fact that levels of (parents’) education have been trending upwards, coming from an educated family increasingly predicts obtaining a higher SAT score. This graph of educational advantage is a Cohen’s d graph with the vertical axis zoomed in. I defined those parents with a bachelor’s or graduate degree as “educated.” (This graph uses the older term for the critical reading subtest, verbal.)
Parents’ education and income show clear links to SAT scores, but so do many other variables. When I mapped state SAT scores, I discovered that Midwestern states achieved higher scores than other states because a small percentage of studious Midwesterners took the SAT, and most other college-bound students in those states only took the ACT. Simple linear regression of state SAT scores with only participation rate as the predictor variable explains 78 percent of variance (P = 10-273). Usually psychology research conducts this kind of analysis with a sample population, but I cannot access the College Board’s raw data, obviously. I am trying to reverse-engineer an SAT database with 16 years of state data. However, a single data point for an income category could represent tens of thousands of people or as few as three. Plus, the year could potentially influence scores due to inflation or even societal changes in cognitive abilities, the so-called Flynn effect. I can appropriately control for those variables, but controlling for race would require estimation because racial group proportions are not broken down every year within each income bracket and educational degree. Therefore, I turned income and education levels into continuous variables for multiple linear regression.
For linear regression, I turned income into a continuous variable by dividing the number of students whose parents earn six-figure incomes by the number whose parents earn less than $20,000 per year. I compared results for this income “gap” to an income “divide” based on the number whose parents earn more than $60,000 per year divided by those whose parents earn less. I created a variable for education based on the number whose parents achieved at least a bachelor’s degree divided by the number whose parents did not. The racial variable was the number of whites and Asians divided by the number of another race. Simple linear regression for state population size showed that it was a significant predictor of SAT scores (P=4.3 x 10-47) that explained 22 percent of variance. However, it became insignificant with all further analysis except when the other predictor variables were either participation, year, and income gap or participation, year, education, and income divide with or without race. Year did not produce a significant P value for simple linear regression (P = 0.5) but always did in multiple linear regression of income or education, lowering scores over time like a reverse-Flynn effect. Both income gap and income divide were significant predictor variables in multiple linear regression, but income divide slightly better predicted SAT scores, explaining 86 percent of variance with year and participation variables, compared to 85 percent for income gap with year, size, and participation variables. Multiple linear regression with participation rate, year, income divide, and education explained 90 percent of variance with all variables achieving statistical significance, but the addition of education caused the P value of the income divide to worsen from 10-83 to 10-3. When I added race as an additional variable, the income divide was no longer a significant predictor of SAT scores (P = 0.4). Most of the impact of income on SAT scores stems from its ability to predict parents’ education levels. Multiple linear regression with the remaining significant variables (state sample size, participation rate, year, education, and race) explained 92 percent of SAT variance.
Graphs of actual SAT scores for income brackets and education levels show the distinctiveness of children whose parents have graduate degrees. Trendlines are given with R-squared variances for the highest and lowest categories.
The graphs for income or education with race reach the provocative result that race affects scores more among the lower rungs of society. As the data only represents state racial proportions, the results leave room for debate. For instance, the furthest left data in the graphs below represent Washington, DC, which I actually treated as a state. Higher-income families there are probably more likely to be white or Asian-American than are lower-income families. Many racially diverse states like California have industries or attractions that pull in successful, educated whites. Nevertheless, one could use these results to defend upper-class affirmative-action beneficiaries or to call for a new class-based system to benefit the many poor, but intelligent whites and Asian Americans.
Also of note is the fact that these graphs look totally awesome.
Anonymous (1998). Why Family Income Differences Don't Explain the Racial Gap in SAT Scores The Journal of Blacks in Higher Education (20), 6-8 DOI: 10.2307/2999198
Anonymous (2008). Why Family Income Differences Don't Explain the Racial Gap in SAT Scores The Journal of Blacks in Higher Education (62), 10-12
Ezekiel Dixon-Roman, Howard Everson, & John McArdle (2013). Race, Poverty and SAT Scores: Modeling the Influences of Family Income on Black and White High School Students’ SAT Performance Teachers College Record, 115 (4), 1-33
15 comments:
"The graphs for income or education with race reach the provocative result that race affects scores more among the lower rungs of society."
That would be evidence against a genetic explanation.
Genetics only shows clear and strong influence at the higher rungs of society. This is because it is only after environmental problems are decreased that the genetic impact can be seen.
For the lower rungs of society, environmental problems are still the main influence on IQ. For poor blacks, you have the typical environmental problems of poverty along with the environmental problems of structural racism.
So, going by that conclusion you came to, it supports the data on continuing racial prejudice and bias.
I agree that racial prejudice in society and other environmental problems are one possible explanation or factor. Other factors could be that my variable for race (state Asian and white sample size divided by other groups’ sample size) was more accurate at the lower rungs of society, high-class African Americans could have more European ancestry, genetics contributes to other class differences, and meritocracy is less amenable to lifting up smart but poor whites and Asians compared to other minorities. The fact that parents’ income could not independently predict scores apart from parents’ education and race calls into question traditional left-wing explanations. That parents’ education predicts children’s SAT scores is almost tautological because high SAT scores enable educational advancement.
Hmm.. to me, it seems a bit more likely that what you're seeing is evidence that a certain amount of merit is still required to attain a graduate degree.
Where are these states with the sub 30% non-Hispanic white+Asian population scores by the way? My understanding is that even New Mexico would score more than 40% on this measure.
Thank you for the question. All of the data points below 40% represent Washington, DC. I mentioned that I treated the capital as a state. (I misstated that race was the number of whites and Asians divided by the number who were not white or Asian. That variable actually is the percentage of the state SAT takers who are non-Hispanic white or Asian.) The reason that there are so many data points just for the capital is that every year and every income or education category produced a data point.
I would like to know what you think of this article differentiating castes.
http://akarlin.com/2012/08/the-puzzle-of-indian-iq-a-country-of-gypsies-and-jews/
It seems indian americans on wikipedia are the wealthiest american diaspora. Per household income and academic success is second to non...
This is not about the SAT, but I didn't know where to post this and you don't have a contact email listed.
I noticed that third generation Asian-American scores drop precipitously on the TIMSS/PIRLS (which hereditarians claim is correlated with IQ as much as the SAT and the PISA). In fact, third-generation Asian-Americans score below native-born Whites.
http://i39.tinypic.com/zob4p0.png
This pattern reflects a "third generation decline" among Asian-Americans that has been noted in other studies:
"Using data from recent Current Population Surveys (CPS), this study compares third-and-higher generation with earlier generation Asian Americans and non-Hispanic whites in terms of socioeconomic characteristics and demographics. The findings suggest a “third-generation decline or flattening” for Asian American and white men as well as Asian American and white women. For each of these groups, the mean of years of schooling among the 2.5 and third generations is lower than among the first and second generations. This pattern is most pronounced among Asian Americans. As for wage determination, the generational differentials can be explained by educational attainment and other basic demographic variables. Overall, these results suggest that assimilation beyond the first generation immigrants no longer improves socioeconomic attainments as expected by traditional assimilation theory. Furthermore, in the case of Asian Americans, cultural assimilation across the generations may actually lower educational attainment and thereby reduce wages contrary to traditional assimilation theory."
http://paa2009.princeton.edu/papers/90354
"Shinagawa pointed out another interesting phenomenon; later generation (second, third, fourth, etc.) Asian Americans on average have markedly lower education and income compared to immigrant Asians.
In 2007, Asians earned 33% of PhD’s but only 2% of those were American born Asians."
http://www.ibtimes.com/asian-americans-increasingly-defying-stem-stereotype-246578
A few months ago I posted this information on the blog Occidentalist run by Chuck/John Fuerst and asked for his explanation, but he refused to let my comment through moderation, even though my tone was no different from the one I'm using here. When I asked why my comment failed to appear, he did not reply. The incident has made my deeply suspect his honesty in other matters...
In any case, I would love to hear your thoughts on the above.
Thanks. First of all, the “hereditarian” position is not intelligence is 100% genetic. The conflict between traditional Confucianism and Americanization does not contradict high intelligence heritability. Future generations of Asian Americans might have enough of a critical mass to avoid Americanization, in addition to the H1-B visa influence. Ameircan culture, itself, has become more niche-oriented thanks to technology. Second, sample size can be a serious issue for looking at such statistics for minorities within minorities. Ron Unz thought he found a massive Flynn effect for Mexican Americans using GSS. The graph of the data that I made shows how noisy it is due to low minority sample size in distant years. I could not get 8th-grade TIMSS data for third or later-generation Asians. It said, “Reporting standards not met,” which suggests to me a sample-size issue. In 2010, 66.5% of Asian Americans were foreign-born. They are already a relatively small group compared to the other racial groups. On top of that, there are questions of whether the comparisons are apt. The Chinese Exclusion Act, the Asian Exclusion Act, and various wars and foreign entanglements influence who was Asian American in previous generations. Plus, racial mixing has greatly affected those generations, especially Japanese Americans. I think that whether a test is high-stakes like the SAT or low-stakes like TIMSS makes a big difference. There is little difference between foreign students and Asian Americans on the SAT. Maybe it is relevant that IQ becomes more genetic with age in children and Rushton thought he found evidence of slower development in East Asians. Socioeconomic status would not necessarily exactly follow test scores. Asians used to lag whites on per capita income but be ahead on family income because they had larger families.
Some, like Jason Malloy, insist that gaps in the U.S. are 100% genetic, but thankfully most other hereditarians are not that cocksure and asinine.
re: 3rd gen Asians
3rd generation Asian-Americans are split between Japanese, Chinese, and Filipinos, though not disproportionately among the latter.
Filipino-Americans are a super-selected crowd who perform better than you would expect from the IQ typically assigned to the Philippines. Filipino-Americans actually have a higher median incomes than all Asian groups except Indians:
http://en.wikipedia.org/wiki/Demographics_of_Filipino_Americans#Socioeconomic
Filipinos also have one of the highest intermarriage rates:
“Interracial marriage among Filipinos is not uncommon,[16] as they have the largest number of interracial marriages among Asian immigrant groups in California,[17] only Japanese Americans have a higher rate nationally.[18] ”
If you’re going to suggest that “brain drain through intermarriage” for Asians can cause such a steep decline in TIMSS/PIRLS scores — which I don’t think it can — then you’d have to apply the same logic to Hispanics (which would greatly reduce the White-Hispanic gap in the TIMSS/PIRLS scores), because the Hispanic-White intermarriage rate is about the same as the Asian-White intermarriage rate. On top of that, Hispanic intermarriage is even more assortative than Asian intermarriage, on average.
In Chuck’s own words, back during his HBD skepticism phase:
“The situation is complex because Hispanics, as with Asians, have high rates of exogamy, because the out-mating is assortative (with Hispanics mating up (with Whites) and with Asians mating down (with Whites) — as one would expect given the tendency for assortative mating within populations and the between population differences), and because self ethnic identification is conditioned, in part, by parental ethnic identification. The joint effect of these three factors is a selective ethnic attrition which magnifies across generations. In short, 5th to 7th generation self identifying Hispanics are a negatively selected remnant of a much larger genealogically defined population; the social mobility of self-ID Hispanics is not (necessarily) representative of that of genealogically defined Hispanics, adjusting for genetic and cultural assimilation. Refer to the papers below:
Duncan, B., & Trejo, S. J. (2011). Who Remains Mexican? Selective Ethnic Attrition and the Intergenerational Progress of Mexican Americans. Latinos and the Economy, 285-320.
Chiswick, B. R., & Houseworth, C. (2011). Ethnic intermarriage among immigrants: Human capital and assortative mating. Review of Economics of the Household, 9(2), 149-180.
Duncan, B., & Trejo, S. (2012). The complexity of immigrant generations: Implications for assessing the socioeconomic integration of Hispanics and Asians.”
re: high-stakes vs. low-stakes testing
I could believe that, but again many of your fellow hereditarians insist:
1) The TIMSS/PIRLS is just as good a proxy for IQ as the SAT and PISA.
2) That "motivation" has nothing to do with test or IQ gaps.
There's also the issue of Asians cheating on the SAT, documented by Education Realist, but I'm not sure how much weight to give to those claims...
If your position is more nuanced, then that's good to know, but you may want to shake the others up a bit.
For the record, I'm not a gene-denier or completely unsympathetic to hereditarianism. My own (tentative) conclusions are...
The following gaps almost certainly have a significant genetic component:
Black-White gap
Australian Aborigine-White gap
Ashkenazi-White gap
The first two I base more on the histories of the groups involved and the universally observed deficiencies by numerous people in various times and places, rather than on achievement tests. The last gap is probably of recent provenance and the result of unique selective pressures on Ashkenazis.
The following gaps I'm more suspicious of:
Asian gaps (both East Asian AND Southeast Asian)
some of the Amerindian/Mestizo gaps (when you think about it, it makes no sense whatsoever for the remnants of various Amerindian groups to all have the same average IQ. The hereditarian research on Latin America has often been lazy and sloppy.)
gaps involving certain Middle Easterners: Arabs and Persians
gaps between various European groups
I also think it's likely that groups differ in personality traits, but that's an even more complex topic and difficult to quantify.
On a final note, Amy Chua also remarked on the third-generation decline among Chinese-Americans in her latest book. But I haven't read it, so I don't know if she cites the same data. It does appear to be a consistent pattern though, not one that can be readily dismissed.
Just found this:
http://muse.jhu.edu/journals/jaas/summary/v007/7.1yang.html
As I suspected, the "braindrain through intermarriage" hypothesis is Dead on Arrival:
"For adult Asians as a whole, holding relevant factors constant, the level of educational attainment increases from the first generation to the second generation but declines in the third generation. Moreover, there is a sharp gender difference in trajectory. For Asian women, the same nonlinear pattern as observed in the total sample emerges. For Asian men, the level of educational attainment decreases over generations. These results lend support to the immigrant aspiration hypothesis and the receptive environment hypothesis but challenges the classic assimilation theory. Changes in relative gender equality in status and education opportunity between home and host countries may help explain the gender differences in the path of educational mobility across generations. The result also points to the importance of gender in the study of educational attainment across generations."
For clarity's sake: as you undoubtedly know, there is a gender gap with regard to Asian-White intermarriage. Asian women intermarry at a much higher rate than Asian men. If intermarriage were the cause of Asian-American generational decline, by winnowing away their best brains, then we'd expect Asian female achievement to decline more than Asian male achievement. But that's the exact opposite of what occurs.
Yang also has another paper from last year which documents the third-generation decline *specifically among Chinese-Americans*, but I can't access it yet. This would kill the hypothesis that Filipinos or some other mediocre IQ group is dragging down the average.
“If you’re going to suggest that “brain drain through intermarriage” for Asians can cause such a steep decline in TIMSS/PIRLS scores — which I don’t think it can — then you’d have to apply the same logic to Hispanics”
This is a complicated issue, but there a lot of reasons to think generational comparisons are not “apples and apples.” I think the rate of interracial mixing has been higher for Hispanics in raw numbers but higher for Asians as a percentage of their group. I remember also reading that Asian women were particularly likely to marry whites if they were new immigrants, rather than needing to assimilate first. Steve Sailer pointed out that Census data suggests a changing class to Asian-white marriage. Whereas African-American-white marriages tended to be from poorer classes, Asian-white marriages used to be poorer and now are wealthier. This might be related to “war brides,” who might not have been considered high-class in their native countries. There is no evidence for regression to the mean with white-Asian mixing. Also, I did graph increasing SAT scores for both Asians and Hispanics. It’s just that Hispanics' scores only increased from 1976 to 1990. Asian scores increased from the mid-80s to the present. Chuck graphed NAEP scores over a longer period, which suggests that African-American scores merely recovered from an especially bad period in the 1970s. That might also be true for Hispanics.
“your fellow hereditarians”
I guess I’m a hereditarian in that I basically accept quantitative genetics, which shows significant individual-score heredity. I’m not a psychologist, and I have a hard-science background and bias, so I would prefer to withhold judgment about genetic racial differences in IQ until a decent gene-index is possible. I recently read Rushton’s book. It was more persuasive than I thought it would be. I would make a number of criticisms of Rushton’s ideas, but they wouldn’t match the criticisms of most of his detractors.
“That ‘motivation’ has nothing to do with test or IQ gaps.”
That’s not my view. I just defended Duckworth’s paper to Gregory Cochran. I’m open-minded, and I shall follow the evidence wherever it goes.
“There's also the issue of Asians cheating on the SAT, documented by Education Realist, but I'm not sure how much weight to give to those claims...”
I told Education Realist that I thought he was a crank. I probably shouldn’t be so aggressive online. He is a teacher, and his cheating/gaming hypothesis is based on personal experience. He expected that the ACT Asian advantage would be smaller than that of the SAT, but it isn’t based on my rough calculation.
“If intermarriage were the cause of Asian-American generational decline, by winnowing away their best brains, then we'd expect Asian female achievement to decline more than Asian male achievement.”
Are you suggesting that when Asians marry whites, they stop being Asian? I don’t think that’s even necessarily true of their children. I think most mixed people follow the one-drop rule, although Asians and Eurasians have recently shown more awareness of anti-Asian quotas.
“Amy Chua also remarked on the third-generation decline among Chinese-Americans in her latest book.”
I just searched the word “generation” through the book. I saw a lot of assertions mostly focused on the first and second generations. She mentions that Chinese Americans do better than their IQ would predict, according to James Flynn. She briefly addresses Richard Lynn and The Bell Curve in the notes. The book appears to be very light on data.
Hi there. This is a really good and interesting report and the regression models are excellent. Do you mind sharing your data set or letting me know where I can find the date set you used?
Thank you!
Thank you. I would love to.
The completed regression study is here.
The data supplements are here.
You can verify the data supplements, if you wish, at their source here.
Where is your proof of this? It sounds asinine.
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