In 2002 Richard Lynn and Tatu Vanhanen’s book IQ and Wealth of Nations estimated the IQs of 185 countries. Critics accused them of cherry picking sources, using unrepresentative samples, comparing and combining samples tested on wildly different tests taken decades apart, and daring to think IQ could be measured cross-culturally. And yet despite nearly two decades of opprobrium, those national IQs remain a landmark, cited in countless peer reviewed articles and repeatedly revised.
One way Lynn has validated his numbers is by showing their high correlation with international exams like Programme for International Student Assessment (PISA). Another independent data-set against which Lynn’s numbers can be tested (assuming he already hasn’t done so) is the IEA‘s Trends in International Mathematics and Science Study (TIMSS). Ostensibly an achievement test, the math section resembles an IQ test, and the test is scored so that most countries average between 400 and 600.
Using the score distribution of UK students as a reference group (see technical note below), I converted the scores from 39 countries to IQ equivalents. My source for the TIMMS scores is exhibit 1.2 in this report.
TIMMS score (8th grade math; 2015)
Korea, Rep. of,
Hong Kong SAR
United Arab Emirates
Iran, Islamic Rep. of
Consistent with Lynn’s hierarchy, we find that East Asian countries cluster around the top (Japan IQ 112 to Korea, Repub of, IQ 116), followed by white majority countries (New Zealand IQ 95 to Russian federation IQ 103), followed by Dark Caucasoid countries (Saudi Arabia IQ 73 to United Arab Emirates IQ 90) and lastly sub-Saharan countries (South Africa IQ 73 to Botswana IQ 77). And while Lynn’s data was ridiculed for declaring entire countries “mentally retarded”, it’s perhaps a sign of higher quality data that no country in this data-set averaged below IQ 70 (though most of the poorest countries chose not to participate).
On page 95 of the report, we’re told that only 10% of England’s 8th graders could score 625+, 36% could score 550+, 69% could score 475+, and 93% could score 400+. Subtracting these percentages from 100 gives the following percentiles: 90, 64, 31, and 7 which can be converted to the following IQs: 119, 105, 93, and 78. Now that we have the IQ equivalents of four TIMMS scores, we can make a linear equation converting TIMMS to IQ which is IQ = 0.18(TIMMS score) + 6.5:
I am extremely honored that Davide Piffer (who has a blog) was kind enough to give our community an exclusive interview. While the leading geneticists in academia have explained only about 10% of the variance in IQ (or its proxy education) at the individual level, Piffer working on his own has reported near perfect correlations between the mean IQs of entire ethnic groups and their polygenic scores, making him a rock star in the HBD community. Virtually no one else on the planet is doing this kind of cutting edge research (at least not publicly).
In retrospect it makes perfect sense that aggregated data should correlate much better than individual level data. Imagine you visited every country in Eurasia and asked only the first person you met in each country their height. Such a small sample size (n = 1) from each country would tell you nothing about which individual country was taller than which, but if you averaged all the heights from the European countries and compared them to the average heights from the Asian countries, you’d learn a lot about which continent was taller. That’s because the small sample size at the level of individual countries is multiplied by the large sample of countries in each continent.
It’s the same with genomically predicting IQ. The small sample of single nucleotide polymorphisms (SNPs) sampled in each individual is multiplied by the large number of individuals sampled in each ethnic group, so while individual predictions are weak, group predictions are strong because individual error cancels out in the aggregate.
Below is my exclusive interview with Piffer. The interview has been lightly edited to remove typos and other mistakes. I began by asking him about table 5 in a 2019 paper he wrote. My statements are in red, while Davide’s are in blue.
PP: I’m very impressed by your work. But the correlation between PG score & mean IQ is so high in table 5 of Piffer (2019) that it seems too perfect. What would you say to skeptics who think you cherry-picked SNPs or manipulated your formulas to get such perfect results?
DP: Thanks. I didn’t cherry pick SNPs. I used the polygenic score provided by Lee et al and you can see that different PGS construction methods lead to same results… I used EA, EA Mtag, etc, weighted and unweighted..they all give same results. Also my paper replicates my previous findings and what I had predicted from theory years ago. The IQs aren’t cherry picked either because I used the same as I used in previous papers to avoid post hoc results.
PP: In table 1 of Piffer (2019), Peruvians & Colombians seem to have higher polygenic scores than the black populations, yet in Figure 11, Africa scores higher than the Americas. So who has higher polygenic scores: sub-Saharan Africans or Amerindians?
DP: Peruvian and Colombian aren’t pure. They are substantially mixed with Europeans. The groups in figure 11 are natives, so they better reflect the unadmixed population. Also the latter are from low coverage genomes with fewer markers so less reliable. I am working on a high coverage version of same datasets but it will take a while due to my limited funds.
Do you have some basic experience in bioinformatics? I am just looking for someone who could run the code on their laptop because it’s taking me a week to impute each chromosome. So I need to run it on multiple computers. But hey no bother…I will do it myself, it will just take it longer.
PP: No sadly I do not have experience with bioinformatics. But I can ask my blog & twitter readers if anyone has such experience and is willing to volunteer their time.
On table 5 of Piffer (2019) the African American PGS (GWAS sig) is 1.836 lower than the NW European PGS. But since African Americans are only 76% non-white (Bryc et al. 2015), can we roughly infer that un-mixed blacks would be 1.836/0.76 = 2.416 below NW Europeans, giving them a PGS score of 46.834?
DP: yes…also you have unmixed native Africans in the other tables. Kenyans, Yoruba, Mende Sierra Leone, etc
PP: In table 5 Latinos have a PGS (GWAS sig.) of 48.654. Do you think this could be used to estimate the PGS of unmixed Amerindians because according to Bryc et al, 2015, Latino Americans are 65.1% white (mostly southern European), 6.2% black, 18% Amerindian, and 11% unassigned, though the unassigned is broader East Asian/Amerindian so should probably be counted as Amerindian. Since you report the PGS for Southern Europeans and since I estimate the the PGS for pure blacks at 46.834, using simple algebra, I estimate unmixed Amerindians would have a PGS of 47.510.
DP: yes, but you should also cross-check these with the other table with scores for Peruvians and Mexicans and see if they converge.
PP: Good point. In one of your data sets you find a 0.57 correlation between PGS and latitude. Do you agree with Lynn’s cold winter theory of how racial differences in intelligence evolved?
DP: in part, yes. but it doesn’t explain the low Amerindian IQ because Native Americans were in Siberia during the Last Glacial Maximum and then they moved to North America at the end of it, which is also a cold region…So I think most of the differences are due to farming and civilization
PP: Well Lynn argues the anomalies can all be explained by population size. Low population races like Arctic people, Amerindians, Australoids, Bushmen, & pygmies have lower IQs than their climates predict because there weren’t enough positive mutations. Meanwhile high population races like East Asians, whites, South Asians, and West Africans have higher IQs than their climates predict. This would also explain why Neanderthals had lower IQs than their climates predict.
DP: but these SNPs are common among the races..the differences are explained by these common SNPs, not pop specific mutations. pop size is probably related to it through higher competition for resources selecting for higher IQ.
PP: I see…so then it was probably farming and civilization as you say. Just as cold climate boosted IQ because it was a novel environment to adapt to, so was farming, civilization and the literacy and numeracy requirements it imposed. Of course Amerindians also independently created civilization but most remained hunter-gatherers.
DP: yes… plus we don’t know how many of these SNPs are just life history or personality traits like C. stuff that farming selected for. most of them are related to g but a subset will also be related to conscientiousness. Emil et al in their Psych paper vetted their association with g in a sample though so I guess they must be genuine associations with IQ for the most part.
PP: Yes, because no one has given a huge sample (n = 1 million) of genotyped people a highly g loaded test. A perfect study would get a sample of 1 million people (from all over the world) and give them an extremely culture reduced test with many subtests to maximize g loading (i.e. block design, draw a person in the sand, name as many body parts as you can in 1 minute in your own language, pictorial oddities etc) and then enter the composite score, DNA and human development index of each person into a computer and have machine learning create a multiple regression equation predicting IQ using HDI & genomic variants as independent variables. By using such a diverse and global sample, one finds the genomic variants that correlate with IQ everywhere and thus are most likely to be causal.
PP: Now that the neanderthal genome has been published, why haven’t you tried to estimate their polygenic score? Richard Klein argues that before about 50 kya, modern humans and neanderthals had similar intellect, but suddenly around 50 kya there was a genetic brain change that allowed modern humans to leave Africa, colonize every continent, replace neanderthals & invent art & complex technology. Testing this hypothesis was the main motivation to sequence the neanderthal genome so there’s enormous interest in their intelligence, even in mainstream science.
DP: yes that’s the next step…we’re analyzing genomes from Bronze age now, but Neanderthal would be good. But funds are limited for this kind of research and I am not working in academia.
PP: Above you rejected Lynn’s population size mutation theory on the grounds that all races have all the known IQ related genomic variants, however it also seems you have no high coverage genomes from low population isolated groups like pygmies, bushmen, australoids, arctic people & pure Amerindians. Is it plausible that high coverage genomes of these groups would show they are missing some of the IQ enhancing mutations that appeared in the last 15,000 years?
DP: What I am saying is that you can see a difference even at the common SNPs in their frequencies. I cannot rule out that they are also missing these mutations but that would be an additional factor.
PP: Do you agree with John Hawks’s theory that positive selection in the last 5000 years has been a hundred times faster than in any other period of human evolution because of the explosion of new mutations & environmental change? This is the exact opposite of Gould who argued we have the same bodies and brains we’ve had 40,000 years ago and all subsequent change has been cultural not biological.
DP: from a purely theoretical point of view, yes, but one would need to study ancient genomes to empirically vet that hypothesis.
PP: Is there any strong evidence in support of Michael Woodley’s theory that white genomic IQ has declined by 10 or 15 IQ points since the Victorian era?
DP: I computed the decline based on the paper by Abdellaoui on British [Education Attainment] PGS and social stratification and it’s about 0.3 points per decade, so about 3 points over a century.
It’s not necessarily the case that IQ PGS declined more than the EA PGS..if anything, the latter was declining more because dysgenics on IQ is mainly via education so I think 3 points per century is a solid estimate
Thank you Davide Piffer for this interview. As mentioned above, you can find more of Davide’s thoughts on his blog.
I decided to look at an excellent study that Lynn had cited. In this study you had 14 pairs of identical twins (one born undernourished, the co-twin born well nourished as measured by birth weight; twin pairs were raised in the same homes). At an average age of 13, they had their head circumferences measured and were given the WISC IQ test.
The heavier twins had crania that were 0.64 cm bigger than their undernourished co-twin. At age 13, the within sex standard deviation for head circumference appears to be 1.31 cm, so that’s a difference of 0.49 standard deviations.
When it came to verbal IQ, the well-noursihed twins and the undernourished twins had the exact same average IQ. And when I saw the exact same average IQ, I mean the exact same average IQ: 98.29 vs 98.29 (unadjusted for old norms)
However when it came to performance IQ, the well nourished twins scored 7.07 IQ points higher than their undernourished co-twins. That’s a difference of 0.47 standard deviations, virtually identical to the 0.49 standard deviation difference in head circumferences.
So it seems that Richard Lynn was half-right. Brain size gains caused by prenatal nutrition do perfectly parallel IQ gains caused by nutrition, but only when it comes to Performance IQ. Prenatal nutrition seems to have virtually zero impact on Verbal IQ, though given the small sample size (only 14 twin pairs), these conclusions are tentative.
It’s amazing how well this study of identical twins perfectly parallels the difference between North American young adults in the 21st century vs circa WWII.
Because humans are cultural creatures, I believe the brain evolved to prioritize verbal ability during times of malnutrition (which as Lynn noted, includes disease since disease prevents the body from using nutrients), so when sub-optimum nutrition shrinks the brain, mostly spatial IQ suffers, and then when prosperity returns you get a genuine Flynn effect, but it’s 100% concentrated in spatial ability. Spatial ability is a luxury of the well fed.
One might wonder why, with all the increasing education and media, I did not find any verbal Flynn effect on the Wechsler. It’s likely that 21st century education gave us an unfair advantage on verbal tests especially Similarities, but this advantage was negated by the fact that a test created in the 1930s was biased against us (especially in tests of specific knowledge). In other words, two conflicting cultural biases cancelled each other out, thus exposing our true verbal intelligence as unchanged since WWII.
Readers of the New York Times have long known that there might be genetically based ethnic differences in IQ, but few people appreciate that nutrition also plays a huge role in IQ. For example, thanks to malnutrition, British whites in the 19th century had real IQ’s around 76 (on modern norms), though this was spuriously pushed down to IQ 66 by lack of schooling (see the Flynn effect). By comparison, in his book Race Differences in Intelligence, scholar Richard Lynn reports the following IQ’s for 10 major populations:
North East Asians: IQ 105
Europeans: IQ 99
Arctic peoples: IQ 91
Southeast Asians: IQ 87
Native Americans: IQ 86
Pacific Islanders: IQ 85
Non-white Caucasoids: IQ 84
Sub-Saharan agriculturalists: IQ 67
Australian aboriginals: IQ 62
Sub-Saharan hunter/gatherers: IQ 54
How much of these scores were affected schooling? Probably not much because virtually all the samples were school children. A major exception being sub-Saharan hunter’gathers, but Lynn estimated their IQ largely by comparing them to equally unschooled neighboring agriculturalist who score IQ 67 with schooling. Since the Bushmen scored about a dozen points lower, it was reasonable to assume that with schooling, Bushmen would score in the mid 50s. Although IQ tests are supposed to measure native ability, few tests are 100% culture fair so it’s necessary to control for schooling when comparing disparate cultures.
So if schooling did not affect these scores, what about nutrition? Although Lynn concedes that malnutrition adversely affects the IQ’s of third-world peoples, no attempt was made to correct the IQ’s for this effect. However on page 184, Lynn provides a table showing the prevalence of malnutrition for various geographic regions. The table lists several measures of malnutrition (i.e. percent underweight, percent wasted, percent stunted, percent anemic) and averaging across the different measures that are provided, implies that as of 1996, malnutrition afflicted 30% of Sub-Saharan Africa, 14% of the Middle East & North Africa, 45% of South Asia, 21% of East Asia & Pacific, and 16% of Latin America & Caribbean. Elsewhere in the book he claims that 25% of Australian aboriginals are malnourished.
I estimated that for each percentage of the population that is nutritionally deficient enough to be proclaimed malnourished, the average IQ of the population is lowered by 0.43 IQ points. This estimate is based on the fact that Lynn notes that African Americans with virtually no white admixture have IQ’s 13 points higher than their genetic counterparts in sub-Saharan Africa, 40% of whom are malnourished. Thus 40 multiplied by 0.43 lowers a population’s IQ 13 points below its potential. So correcting the IQ’s of all the ethnic groups for the level of malnutrition in the regions that they live, gives the following:
Northeast Asians: IQ 105 (no corrections, they live in first world countries)
Europeans: IQ 99 (no corrections, they live in first world countries)
Southeast Asians: IQ 96 (corrected for 21% malnutrition in East Asia & the Pacific Islands)
Pacific Islanders: IQ 94 (corrected for 21% malnutrition in East Asia & the Pacific Islands)
Arctic people: IQ 91 (no corrections, they live in first world countries)
Non-white Caucasoids: IQ 90 (corrected for 14% malnutrition, since they mostly live in the middle east/North Africa)
Native Americans: IQ 89 (many live in Latin America which has 16% malnutrition, others live in first-world North America, I split the difference & corrected for 8% malnutrition)
Sub-Saharan agriculturalists: IQ 80 (corrected for 30% malnutrition in Sub-Saharan Africa)
Australian aboriginals: IQ 73 (corrected for 25% malnutrition mentioned by Lynn)
Sub-Saharan hunter/gatherers: IQ 67 (corrected for 30% malnutrition in Sub-Saharan Africa)