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 Russian Reaction Blog / PsychometricsTeasers

The population of the world’s major regions according to the UN’s World Population Prospects 2017 report.

World Population Prospects (2017) 2015 2050 2100
WORLD 7,383,008,820 9,771,822,753 11,184,367,721
Sub-Saharan Africa 969,234,251 2,167,651,879 4,001,755,801
East Asia 1,635,150,365 1,586,491,284 1,198,264,520
South Asia 1,823,308,471 2,381,796,561 2,230,668,781
South-East Asia 634,609,846 797,648,622 771,527,666
MENA & C. Asia 551,964,576 850,895,914 1,045,856,658
Europe 740,813,959 715,721,014 653,261,252
Latin America 632,380,831 779,841,201 712,012,636
North America 356,003,541 434,654,823 499,197,606
Oceania 39,542,980 57,121,455 71,822,801

Assume the usual S.D.=15, and that their average IQs as of 2017 are as follows: Sub-Saharan Africa 70, East Asia 100, South Asia 80, South-East Asia 85, MENA & C. Asia 85, Europe 100, Latin America 85, North America 100, Oceania 90.

This should look plausible to people who’ve looked at the data. East Asian (Japanese, Korean, Chinese) IQ tends to be higher than 100, usually around 103-105, but I am giving it as 100 because in practice, for unclear reasons, East Asian IQs also tend to be “worth” 5 points less than Euro-American ones so far as economic performance and human accomplishment go.

Anyhow, if we also assume that regional IQs will remain “fixed” for the rest of the century, then the world average IQ will drop from 87 today to 82 by 2100, primarily on account of the massive demographic expansion of Sub-Saharan Africa.

However, fortunately, the number of people belonging to smart fractions” – which I will denote as people with an IQ above 160 (the approximate level that you have to be at to be capable of contributing to elite scientific progress today) – will remain similar to today, though it will be negatively impacted by demographic decline in Europe and East Asia.

Smart Fractions (No Flynn) 2015 2050 2100
WORLD 87,196 87,580 75,397
Sub-Saharan Africa 1 2 4
East Asia 51,787 50,246 37,951
South Asia 88 115 108
South-East Asia 182 229 221
MENA & C. Asia 158 244 300
Europe 23,462 22,668 20,690
Latin America 181 224 204
North America 11,275 13,766 15,810
Oceania 61 87 110

But what happens when we adjust for the FLynn effect? In his 2016 survey of psychometrists, Heiner Rindermann and co. compiled the following expert assessments.


This leads to a massive increase in the number of smart fractions, almost entirely on account of East Asia.

China as a now fully developed country drives global scientific progress pretty much single-handedly, like Europe did in the 19th century.

IQ Flynn (Rindermann) 2015 2100
WORLD 87,196 294,485
Sub-Saharan Africa 1 63
East Asia 51,787 245,857
South Asia 88 1,266
South-East Asia 182 1,181
MENA & C. Asia 158 1,155
Europe 23,462 27,364
Latin America 181 1,504
North America 11,275 15,810
Oceania 61 285

That said, I don’t think those FLynn projects are realistic, in part because East Asia is projected to increase in IQ so incredibly fast even though it is already a reasonably well developed place.

China itself can still probably eke out 3-5 IQ points, but Chinese fertility has been dysgenic since the 1960s, so this won’t last. I suspect East Asia – which in demographic terms is pretty much just China – will remain at a consistent level, with FLynn and dysgenics canceling each other out over the course of the century.

What if we use the following estimates for IQ changes during the 21st century (broadly justified here):

  • +10: Sub-Saharan Africa, South Asia
  • +5: South-East Asia
  • 0: East Asia, MENA & Central Asia, Latin America
  • -5: Europe, North America

Resulting table of smart fractions in 2100:

IQ Flynn (AK) 2015 2100
WORLD 87,196 51,726
Sub-Saharan Africa 1 193
East Asia 51,787 37,951
South Asia 88 3,414
South-East Asia 182 1,181
MENA & C. Asia 158 300
Europe 23,462 4,797
Latin America 181 204
North America 11,275 3,666
Oceania 61 21

So what has basically happened is that smart fractions plummet in the high-IQ world due to a combination of demographic decline, dysgenic fertility, and low-IQ mass immigration.

Meanwhile, the quantity of smart fractions from the Global South will rise, due to some FLynn catchup, but absolute numbers will remain modest.

Overall, this is a pretty catastrophic outcome.

Not only do we see a halving of 160+ IQ smart fractions, but it is also very likely that the threshold for new scientific discoveries will have risen in the meantime, since problems tend to get harder, not easier as you climb up the technological tree.

For instance, if by 2100 the new “discovery threshold” is at an IQ of 175, the people still capable of driving global science forwards might number in the mere hundreds, in a world of more than ten billion.

The likely end result of this would be an end to scientific progress, and eventually, the Age of Malthusian Industrialism once a technologically stagnant and progressively more fecund world bumps up against the limits of the industrial economy.



I don’t know how, but Lynn, Cheng, and Russian psychometricist Grigoriev have managed to find Russian regional results for PISA 2015.


Moscow has plummeted in the rankings and is now fourth, whereas Saint-Petersburg is now first.

I have calculated the correlations with the PISA 2009 results, for regions that participated in both surveys, to be a pretty weak r=0.52. As you can see, the samples for each region are pretty small, typically around 100, though relatively more schoolchildren were tested in the capitals: 245 in Saint-Petersburg, and 373 in Moscow.

The Yakut-majority Sakha Republic has improved drastically, by half an S.D., so it is no longer last, but modestly below average (this ties in with Vladimir Shibaev’s recent work in 2017 which shows that Yakut IQ might be similar to Russian, and not drastically lower, as an earlier study from 2015 had indicated). That “honor” now belongs to Dagestan, which remains stuck at a PISA-equivalent IQ in the high 80s.


Lynn et al. also did their standard correlation exercises.

Other tests of academic achievement (average Unified State Exam results of those admitted to universities from 2014) and historical literacy (1897 census):

Note in particular that the province of Dagestan has the lowest PISA score (424.1) and the second lowest EQ (84); and also that the city of St. Petersburg has the highest PISA score (524.4), the highest EQ (111) and the highest literacy rate in 1897 (61.6%). The city of Moscow has the fourth highest PISA score (516.4), the second highest EQ (110) and the second highest literacy rate in 1897 (53.1%).

GDP per capita:

Second, the PISA scores were correlated at r = .31 with GDP per capita. The correlation falls just short of statistical significance at p<.05 (r = .32 would be statistically significant).

wealth-iq-russia This is because some Russian regions have resource windfalls amidst low populations, e.g. Khanty-Mansyisk AO, which accounts for half of Russia’s oil output and enjoys a Swiss-like standard of living.

If you only consider “normal” Russian regions, the correlation becomes a much more typical r=0.73 (the graph to the right is based on results from PISA 2009 and PPP-adjusted Gross Regional Products from 2008.

Russian ethnicity:

Third, the PISA scores were significantly correlated at r = .45 (p<.01) with the percentage of the population with Russian ethnicity. This result is confirmed by the multiple regression analysis showing that the percentage of Russian ethnicity was a significant predictor of the PISA scores (β = .36, t = 2.68, p<.01).

Cold winters:

Fourth, the PISA scores were significantly correlated at r = .35 (p<.05) with latitude showing that IQs are higher in the more northerly provinces.

• Category: Race/Ethnicity • Tags: IQ, Paper Review, Psychometrics, Russia 


Grigoriev, Andrey & Lynn 2009
Studies of Socioeconomic and Ethnic Differences in Intelligence in the Former Soviet Union in the Early Twentieth Century


This paper reviews the studies of socioeconomic and ethnic and racial differences in intelligence carried out in Russia/USSR during the late 1920s and early 1930s. In these studies the IQs of social classes and of ethnic minorities were tested. These included Tatars (a Caucasoid people), Chuvash and Altai (mixed Caucasoid-Mongoloid peoples), Evenk (a mixed Caucasoid-Arctic people), and Uzbeks (a Central-South Asian people). The results of these studies showed socioeconomic differences of 12 IQ points between the children of white collar and blue collar workers, and that with the exception of the Tartars the ethnic minorities obtained lower IQs than European Russians.

This is essentially a short history of psychometrics in the USSR/Russia.

(1) The first measurement of Russian IQ was performed in 1909 by A.M. Schubert, who used the French Binet test with n=229 children: “She concluded that the Binet test appeared to be too difficult for Russian children and the scale should be moved on 1 to 2 ages to be appropriate for them.” Since Mental age ÷ Physical age × 100 = IQ, this implies their average IQ was perhaps one S.D. lower than that of the French, though later researchers pointed out those children were drawn from lower socio-economic strata.

In 1930, now in the USSR, another study found the following:

They tested 414 children aged between 8½ and 11½ with the American Stanford– Binet (administered in Russian translation). The sample consisted of 200 children of peasants,141 children of blue collar workers, and 73 children of white-collar workers. All children were from Moscow or the Moscow region. The results were that the children of peasants obtained a mean IQ of 87 (the standard deviation=10), the children of blue-collar workers a mean IQ of 91 (SD=8.6) and the children of white-collar workers a mean IQ 98 (SD=8.4). The mean IQ (unweighted) for three groups was 92… Thus, the total weighted mean for Russian children in this study was 90.3 (these IQs are in relation to American Stanford–Binet norms).

Capture This brings to mind a 1920s study quoted by Anne Anastasi in her book Differential Psychology (pp.524), in which Russian immigrant children to the US got 90.

This 10 point difference was presumably there because Russia was a more economically backwards country, with a more repressed average IQ due to gaps in schooling, malnutrition, parasitic load, etc.

(2) As in the West, consistent differences were found in the IQs of people from different socio-economic strata.

Another study of relation of IQ to social class was carried out by M. Syrkin (М.Сыркин)(Сыркин,1929) who compared the intelligence of fourth grade children (N=338, age approximately 10 years) belonging to six socio-economic groups. The lowest group was described as “ blue collar workers and at least one of parents illiterate”and the highest group was described as “white-collar workers and at least one parent educated in an institute of higher education”. Intelligence was assessed with five verbal tests measuring comprehension and verbal reasoning. There was a difference of 1.42d(equivalent to 21.3 IQ points) between the lowest and highest socioeconomic groups.

The USSR really did expel, kill off, or otherwise limit the reproductive fitness of its best and brightest.

In 1928, E.I. Zverev (Е.И. Зверев)(Зверев, 1931) tested the IQ of 114 children just admitted to school and aged about 7½– 8 years, in and around the city of Kursk, about 500 km south of Moscow. The children were tested with the Binet– Bert test (a Russian adaptation of the Binet). The mean IQ of these children was 80.8. This is much lower than the IQ of children obtained by Gurjanov, Smirnov, Sokolov, & Shevarev (Гурьянов, Смирнов, Соколов,&Шеварев, 1930) for Moscow and the Moscow region. Probably this difference was due to methodological and sample differences, but there is a possibility that the regional factor was also involved.

The latter hypothesis is likely the correct one.

In the 2009 PISA test, there was a 12 IQ point difference between Kursk and Moscow, which is an incredibly concentrated cognitive cluster.

(3) Now we go on to the most “controversial” part – ethnic differences in IQ.

Central Russia

There were also some studies of the IQs of non-Slavonic but predominantly Caucasoid peoples.I. Bektchentay (И .Бикчентай) and Z. Carimowa (З.Каримова )(Бикчентай &Каримова, 1930) tested the IQs of 380 Tartar children aged 8– 18 in fi ve Tartar schools in Moscow with the Boltunow–Binettest(aRussian adaptation of the Binet). The Tartars are indigenous to the Caucasus in the far south of Russia and the former Soviet Union, but a number of them live in central Russian towns and cities. The mean IQ of the Tartar children in this study was approximately the same as that of Russian children. The correlation between the Boltunow– Binet test and school achievements (assessed by teachers’ estimates) in their study was 0.84.

Yes, this is a pretty major distinction.

The Volga Tatars – the Muslim and Christianized Tatars of central Russia – have an average IQ of around 100 (about equal to modern Russia/Europe). Population genetics studies have found them to be basically acculturated Slavs.

The first of these was reported by F.P. Petrov (Е.П. Петров) (Петров, 1928) who tested the IQs of 1398 Chuvash children aged 3–13 in 1926–1927 with the French Binet–Simon test… The figures inTable 2 show a median IQ of 87 for boys and 84 for girls, and means (unweighted) of 89 for boys and 86 for girls. These are in relation to 100 for French norms, but no normative data are reported for Russian children. The IQs of the Chuvash children show a decline with age, with the lowest IQs among the 12 and 13 year olds.

Chuvashia is currently about average for the Russian regions.


Also tests carried out on indigenous tundric peoples, such as the Evenks (Bulanov 1930):

The results are presented as typical for Evenk children, but because of the small samples, their IQs may not be regarded as reliable. The results are as follows. For the Binet test the mean IQ was 70.16 (for 5 children, and in relation to French norms). The results obtained with the Rossolimo test showed lower average IQs of the Evenk (Tungus) compared with a Moscow sample on some abilities, namely, memory for pictures and words, ability to comprehend combined pictures, ability to comprehend visual incongruities, and, according to Bulanow’s interpreta- tion, ability to retain a high level of attention. As regards memory for pictures, the results contradicted the sometimes described capacity of Evenk (Tungus) to remember exactly long routes on wild territory (Encyclopedic Dictionary by Brockhaus & Efron (Энциклопедический словарь Ф .А . Брок – гауза и И.А .Ефрона ), 1902, vol. 67, p. 66)….

Bulanow also reported some observations on Evenk (Tungus) children and adults concerning their great difficulty in understanding the concepts of measurement and number. He reported that when Evenk children were questioned about devices for measurement, they did not have the concept of an absolute unit of measurement. They thought that the unit changed with the material measured. Bulanow reported further that when he asked Evenk adults how many children they had “ It was difficult, almost impossible, to get from parents precise information as to how many of their children were alive, how many of their children had died, what was the age of their children, and so on.” (p. 198).

… and on the Altai (Zaporochets 1930):

The results for the Binet test were as follows: mean IQ for total group was 66.9 (sd. 8.5), mean IQ for children aged 8– 12 was 69.15, and the mean IQ for children aged 13–16 years was 64.8. As noted by Zaporojets, this test was tedious for the Altai children. Some tasks were especially difficult for them. These were tasks involving calculation, logical operations, and the fluency task to name as many as words as possible during 3 min. As for the Rossolimo test, the most diffi cult tests for Altai children were those requiring the ability to retain a high level of attention and to comprehend visual incongruities. Their mean IQ for the Pintner–Peterson test was 75.

Zaporojets noted that the Altai children did not have a clear understanding of units of measurement. He observed that when they were questioned about the length of a meter, the Altai would often ask: “Which meter?”They thought that the meter in one shop could be longer than in another. An adult Altai said about distance: “It is 100 big versts (approximately 100 kilometers)” (he apparently thought that the number of small versts must be more).

Zaporojets’ paper contains some interesting observations on adult Altai. Although adult Altai performed calculations poorly at the time of study, they showed a remarkable ability for visual estimation of large quantities. A herdsman, who could count only to 20–30, noticed very well the absence of one horse, cow or sheep in a herd of many hundreds. He looked at a huge herd and noted that a particular cow was absent. Another example of the great visualization ability of the Altai was that they could remember and showed the way through wild territory, where they had been only once many years previously.

Common theme: No numeracy (they’d have a very bad Whipple’s index), very premodern and non-abstract ways of thinking, but quite well suited for their environment.

In PISA 2009, Yakutia had the lowest score of any tested Russian region, including Dagestan (though Chechnya and Ingushetia were not included). Ethnic Yakuts, who probably have similar IQs to the Altai and Evenks, constitute 50% of its population, though probably more like 2/3 amongst the children taking PISA due to their higher fertility rates. This might imply that the average Yakut IQ is in the low-to-mid 80s.

Central Asia

First test was carried out in 1926 by A. Schtelerman: He did not give IQs but reported that the scores of the Uzbek children were lower than those of children in Moscow.

A series of studies by V.K. Soloviev on Russian and Uzbek army cadets and professionals found that “the test scores and the educational level of the Uzbeks were lower than those of the Europeans.”

The third study of the intelligence of the Uzbeks was carried out in 1931 by A.R. Luria (А.Р . Лурия ), at that time at the Institute of Psychology in Moscow. Luria did not use intelligence tests but gave a descriptive analysis of the Uzbeks’ cognitive abilities. He distinguished two modes of thought designated graphic recall (memories of how objects in the individual’s personal experience are related) and ca- tegorical relationships (categorisation by abstract concepts). He found that the thought processes of illiterate Uzbek peasants were confined to graphic recall and that they were not able to form abstract concepts. For example, they were shown a hammer, an axe, a log and a saw, and asked which of these did not belong. The typical Uzbek answer was that they all belonged together because they are all needed to make firewood. People who are able to think in terms of categorical relationships identify the log as the answer because the other three are tools (an abstract concept). Illiterate Uzbeks peasants were unable to form concepts of this kind. They were also unable to solve syllogisms. For instance, given the syllogism “There are no camels in Germany; the city of B is in Germany; are there camels there?” Luria gave as a typical Uzbeks answer “I don’t know, I have never seen German cities. If B is a large city, there should be camels there.” Similarly, Luria asked “In the far north, where there is snow, all bears are white; Novia Zemlya is in the far north; what color are the bears in Novia Zemlya?”. A typical Uzbek answer was “I’ve never been to the far north and never seen bears”(Luria,1979, p. 77–8). Thus, Luria concluded that these peoples were not capable of abstract thought: “ the processes of abstraction and generalization are not invariant at all stages of socioeconomic and cultural development. Rather, such processes are pro- ducts of the cultural environment” (Luria, 1979, p. 74). Luria proposed that the ability to think in terms of categorical relationships is acquired through education. He did not suggest that the Uzbeks have any genetic cognitive deficiency.

I wrote about Luria back in the late 2000s when I still agnostic about genetic racial differences in IQ.

Today those factors no longer really hold, but Central Asians do very poorly on international standardized tests.

Kyrgyzstan came at the very bottom of PISA 2009, with a PISA-equivalent IQ of around 75.

Table below is from David Becker’s database of national IQs:

National Ethnic Age N Test IQ Study
Kazakhstan 8 to 16 617 SPM+ 87.30 Grigoriev & Lynn (2014)
Kyrgyz 85.60 Lynn & Cheng (2014)
Tajikistan 13 to 15 674 SPM+ 88.00 Khosimov & Lynn (2017)
Uzbekistan 10 to 15 51 SPM+ 86.00 Grigoriev & Lynn (2014 )
Uzbekistan 11 to 13 614 SPM+ 85.00 Salahodjaev et al. (2017)

Still, Luria has some of the best arguments against that position, so its a bit surprising that the blank slatists don’t cite him more.

stalin-the-tajik(4) Or maybe not, because it still didn’t save him him from the SJWs’ ideological predecessors, Sovok Justice Warriors:

These early studies carried out in the years 1926– 1931 found that there were substantial socioeconomic and ethnic/ racial differences in intelligence in the Soviet Union. These conclusions were not consistent with Marxist orthodoxy which held that these differences would disappear under communism. Accordingly, these studies, particularly that of Luria, attracted a great deal of criticism in the Soviet Union in the early 1930s. This has been described by Kozulin (1984): “Critics accused Luria of insulting the national minorities of Soviet Asia whom he had ostensibly depicted as an inferior race. The results of the expedition were refused publication and the very theme of cultural development was forbidden” . In 1936 intelligence testing was banned in the Soviet Union. It was not until the 1960s and early 1970s that this prohibition was progressively relaxed (Grigorenko & Kornilova, 1997). Luria’s work was not published in Russian until 1974 and English translations were published in 1976 and 1979 (Luria, 1976, 1979).

As Lynn and Grigoriev point out, this was closely correlated to the suppression of genetics research, though at least Luria and Co. weren’t outright murdered like Vavilov.

The history of work on intelligence in the former Soviet Union parallels that of genetics, where mainstream Mendelian theory represented by Nikolai Vavilov in the 1920s was likewise suppressed in the 1930s and replaced by the environmentalist pseudo-genetics of Trofi m Lysenko. The domination of science by political theory was relaxed in the 1960s and 1970s, and in recent decades both intelligence research and Mendelian genetics have been rehabilitated in Russia.

Scientifically, there is real work being done on psychometrics in Russia, though in comparison to the US it is very meager and basically inconsequential.

Since it is not politicized in the US, it is neither promoted nor prosecuted.

If psychometric considerations were to move closer to politics, e.g. by tying them to the hot potato that is Central Asian immigration, things can go any which way. Although Russians have a more commonsense take on these matters – if 25% of Americans seriously think intelligence is a “social construct,” it’s probably more like 5% in Russia. On the other hand, the Leftists, Stalinists, and even many Eurasianists are aggressively opposed to the idea that intelligence is heritable and differs significantly between races, and in the event that the authorities side with them, Russian scientists don’t have the First Amendment or an fair and impartial court system to hide behind.



Ritchie, Stuart – 2017 – Review of The Rationality Quotient by Stanovich et al.


From Stuart Ritchie’s review of “The Rationality Quotient” by Keith Stanovich et al.:

But it was the reported correlation of the [Comprehensive Assessment of Rational Thinking] with IQ-type tests that was really unexpected, given the authors’ argument that they measure very different constructs. A cognitive composite—made up of tests of analogies, antonyms, and a word checklist (Table 13.11)—was found to have a correlation with the full-scale CART of 0.695. 0.695!

That’s the extent to which actual IQ tests typically load on the g factor and each other. One might even go so far as to propose that rationality is intelligence.

The notion that intelligent people are more prone to irrationality is a cognitive bias, though a very understandable one. The Newton who obsesses over the occult is just considerably more noticeable than some nutter ranting about the End Times.

Greg Cochran counters that Western intellectuals were more likely to fall for “destructive nonsense” than plumbers during the 20th century. I suspect that was more due to intellectuals not understanding plumbers, neither then nor now, rather than any failure of rationality per se. In everyday life, people tend to associate with people of similar intelligence, and have a social circle of about 150 friends and acquaintances.

And guess what? Communism works great within monasteries and universities.

• Category: Race/Ethnicity • Tags: Paper Review, Psychometrics, Rationality 


Whitley, Elise et al. – 2016 – Variations in cognitive abilities across the life course



New paper by Elise Whitley et al. on age and sex differences in IQ for n=~40,000 British sample.

  • Five tests: Word recall, verbal fluency, and subtraction (loading ~0.5 on g), and number sequence and numerical problem solving (loading ~0.7 on g).
  • Males score about 4 IQ points more on the derived g-factor of cognitive ability.
  • … though this result should be treated with caution on account of: (a) g having different structure across the sexes; (b) it is not an exception to a common problem in IQ and sex studies, namely, the undersampling of men with lower cognitive ability.
  • Better subjective health was associated with higher IQ.
  • The overall pattern across age was a plateau from the late teens to age 65, then a steep fall soon thereafter.

I would say that the ultimate and really the only reason we have mandatory retirement policies are cognitive ones.

EDIT: Emil Kirkegaard had a closer look at the results, including a nicer graph of the age/sex results:

My guess is that the intercept bias/invariance has to do with the composition of the battery. There were only 5 tests, and their breakdown was: 3 math, 1 verbal, 1 memory. Women had better memory but there was no difference in verbal fluency (this is a common finding despite what you have been told). So, the problem likely is that the g factor is colored because 60% of the tests were about math, and that men have an advantage on the math group factor.



There is a new expert survey out which, amongst other things, queries the world’s top psychometrics experts on the future of the FLynn effect (Flynn + Lynn – clever).

future-FLynn-effect-to-2100 James Thompson has a summary at his column.

The two most important reasons for the end of the FLynn effect in the West are regarded to be “low intelligent more children” (henceforth, “dysgenics“) and migration.

Here is my take (assuming no human genetic editing, neural augs, etc).

East Asia – +0. Have no idea where the high end estimates come from – Japan and Korea are already fully developed and have maxed out their FLynn potential, while China’s indicators on education, nutrition, and social well-being – as is typical in Communist countries – are considerably ahead of its GDP per capita. And the former are more important for IQ than pure wealth. I suspect any further marginal FLynn gains will be canceled out by dysgenics, which have been acting on China since the 1960s (Wang et al., 2016).

India – +10. Currently around 80 according to both IQ tests and PISA. I suspect India’s average genotypic IQ is ~95, though strongly differentiated by caste. However, the dysgenics trend seems to be strong, acting via both region (dirt poor and highly illiterate Bihar is the most fertile, while Kerala with its competent governance and historical achievements in mathematics is the least fertile) and caste (scheduled castes have highest fertility, while the Brahmin share of the population is declining since at least the 1930s).

Africa – +10. Currently around 70-75, suspect it “should be” 85-90, but doubt Africa will actually develop enough socio-economically to fully max out its potential FLynn effect.

Latin America – -3. Few of these countries can be described as truly Third World, especially the more significant ones, and nutrition is quite adequate (e.g. Brazil consumes as much meat per capita as Germany). As such, I suspect most of its FLynn gains have already been actualized! Meanwhile, dysgenic trends amongst the elites are strong, while the lower IQ, more indigenous underclass continues to expand rapidly.

Arab/Muslim countries – -3. A lot really depends on whether they start to seriously clamp down on first cousin marriages, which could raise IQs by as much as 10 points. A few like Tajikistan are taking this seriously, but most are not, and first cousin marriages remain stubbornly high. As such, Arab and Muslim IQs will probably decline due to dysgenics and brain drain arising from future geopolitical convulsions (according to some calculations, solar is already reaching cost parity with fossil fuels; what happens when countries like Saudi Arabia lose their oil rents?).

Australia – +0. Agree with the FLynn experts – any modest dysgenics are cancelled out by their cognitively elitist immigration policy.

Eastern Europe – -3. Less likely to be inundated with Third World immigrants, at least so long as Germany doesn’t become a total dump, but East-Central Europe has already maxed out Flynn, continues to experience brain drain, and Hungary, Romania, and Bulgaria in particular have a Gypsy problem. Russia and Ukraine might gain a couple of points if, as expected, their Soviet-legacy alcoholization epidemics continue to recede; but Russia, in particular, has immigration issues of its own (Central Asia = Mexico), while Ukraine is bleeding out brains and will in all likelihood long continue to do so. Finally, as in Western Europe, fertility patterns are dysgenic in all these countries.

Israel – -5. Will probably plummet as duller nationalists and the religious continue outbreeding seculars, plus brain drain.

Canada – -3. Cognitively elite immigration policy like Australia, but annul their own efforts by importing Somali refugees.

Scandinavia – -4. Sweden Yes!

West-Middle Europe – -4. Strong dysgenics, and huge IQ hit from immigration, but at least for now gets many of the more intelligent Mediterranean Europeans.

West in general – -4.

Southern Europe – -6. Triple whammy from Third World immigration, brain drain to northern Europe, and possibly the most strongly dysgenic fertility patterns in the world.

USA – -3. Latin America will of course continue exerting downwards pressure, but dysgenics amongst White Americans is relatively mild, it attracts the world’s cognitive crème de la crème, the Hispanic baby boom has subsided following the Great Recession, and Trump is promising a Big Beautiful Wall. So I am considerably more optimistic about the US than most. Furthermore, if Europe truly goes belly up, the US may even get a big cognitive boost from the richer Europeans fleeing the fruits of their earlier political choices.

• Category: Race/Ethnicity • Tags: Flynn Effect, Futurism, Psychometrics 

Now that we have established that immigration is not much good, let’s take a look at another component undergirding our transition to Idiocracy – the differential fertility rates of different IQ groups.

This is a highly contentious topic, and not just on account of the usual political kurfuffles, but also on real disagreements as to its actual extent. Psychologists such as Richard Lynn, Edward Dutton, and Michael Woodley are pessimistic (Woodley 2014; Dutton et al. 2016). OTOH, JayMan has argued based on WORDSUM analysis that “Idiocracy can Wait.” This topic is extra difficult because you also have to disentangle the dysgenics trend from the Flynn effect that has raised IQs in the developed by about 10 points during the 20th century.

The PISA Data Explorer is truly an invaluable tool for bringing the light of cold, hard facts on these issues.

While playing around with it, I noticed you can select the variable “same age siblings,” which ranges from zero to ten. Zero siblings implies, of course, that the student in question is an only child; by definition, the survey excludes entirely the childless portion of the population, which is also its brightest. Data only exists for the Mathematics part of PISA 2000, but it is more than enough to get an idea of the general trend – and as you might expect, it’s not a very good one.

I calculated the “slope” in terms of PISA-adjusted IQ points lost per additional sibling for the first four siblings (in practice, since TFR <<6 for all countries in PISA 2000, the IQ of children from even larger families won’t have much of an effect). See the table at the bottom of this post.

Here are some general points to take away:

(1) Indonesia is the only country, at least as judged from the Math portion of PISA 2000, that has eugenic fertility patterns (since its a developing country with a TFR = c.2.5, we can be pretty sure that childlessness will not impact these statistics down by very much since its simply very rare). Second is Thailand. Both are lower-middle income Asian countries that only escaped the Malthusian trap within living memory and are in the middle stages of the demographic transition. (That said, in PISA 2015, coverage of the 15 year old population was not great in either country – 68% in Indonesia, 71% in Thailand – and assuming that was also generally true in 2000, those not turning up are sure to be less bright and will probably come from more rural, bigger families).

[Epistemic status: Speculative]. However, despite also being within the middle-income brackets, the Latin American countries have moderately dysgenic fertility patterns. I wonder if this could explain Steve Sailer’s observation that Latin American countries seem to have smaller smart fractions than Middle Eastern ones, despite similar average IQs. Maybe their European and, critically, Europeanized, upper classes have simply failed to reproduce in the last couple of generations?

(2) The East Asian and European Nordic states have more eugenic fertility patterns. The European Mediterranean – Greece, Italy, Romania, Portugal, Bulgaria – has some of the worst. France, Spain, Brazil, the UK, Germany, Poland, Russia, and the US all cluster close to each other (though American White fertility is probably more eugenic, perhaps around Australia’s and Canada’s level, since minority and especially Black fertility patterns are known to be highly dysgenic even according to JayMan’s optimistic analysis).

(3) The rate of childlessness is considerably lower, at around 10%, in the ex-Soviet bloc and East-Central Europe than in Western Europe and the US.


This means that their real figures will get a modest boost relative to those of Western Europe, since not as big a percentage of the professional class are getting cut out entirely.

(4) You can’t precisely quantify the dysgenic impact from this with any exactitude, since you’ll also need to combine it far more detailed fertility data.

That data does exist, at least for many of the OECD countries and Russia, so its doable, but it would be a pretty big project.

(5) Eyeballing it there seems to be a moderate degree of correlation with commenter Cicerone’s country estimates of dysgenic fertility extracted from fertility data of educational classes.


IQ vs. #Siblings

Country #0 #1 #2 #3 #4 b
Indonesia 78 82 83 81 80 0.37
Thailand 88 91 90 89 88 -0.16
Japan 103 104 103 103 102 -0.48
Ireland 104 106 106 104 102 -0.51
Iceland 103 102 101 101 100 -0.59
Denmark 99 101 100 98 97 -0.70
Finland 108 108 107 107 105 -0.70
Norway 101 102 102 101 98 -0.71
Sweden 102 104 104 102 99 -0.83
Korea 103 104 103 102 100 -0.88
Chile 87 88 88 85 84 -0.93
Israel 95 96 97 94 91 -0.94
Canada 106 106 105 105 102 -1.07
New Zealand 103 107 106 104 99 -1.13
Australia 105 106 105 102 101 -1.13
Peru 75 80 79 74 71 -1.27
Mexico 89 94 92 88 85 -1.37
Switzerland 99 100 100 98 93 -1.42
Austria 100 100 99 97 93 -1.69
Latvia 95 96 94 91 89 -1.70
Albania 76 81 79 75 70 -1.83
France 102 102 102 98 95 -1.86
Spain 101 100 98 96 94 -1.88
Brazil 87 88 86 83 80 -1.93
United Kingdom 107 106 104 102 99 -1.93
Germany 99 100 97 92 93 -1.93
Poland 101 99 97 92 94 -1.95
Russia 98 96 92 90 90 -2.01
United States 103 105 102 99 96 -2.01
Luxembourg 94 93 91 89 85 -2.17
Hong Kong 106 105 103 101 96 -2.41
Belgium 103 104 102 99 93 -2.45
Czechia 101 101 98 95 91 -2.63
Greece 101 97 95 93 90 -2.66
Hungary 99 99 96 92 89 -2.75
FYROM 80 84 78 72 72 -2.84
Romania 93 92 88 85 81 -3.03
Italy 102 99 96 94 89 -3.03
Bulgaria 92 91 85 83 80 -3.19
Portugal 100 97 94 92 87 -3.20
OECD Average 101 101 99 97 95 -1.57
Total Average 97 98 96 94 91 -1.64


• Category: Race/Ethnicity • Tags: Dysgenic, Fertility, IQ, Psychometrics 

The commenter “m” did some calculations to work out the relative performance of different countries in PISA vs. TIMSS, and in Math vs. Science.


m writes:

Dimension 1 is overall performance across all 4 (PISA Math, PISA Science, TIMMS Math, TIMMS science). Everything goes up with this dimension. Highest performers: Singapore, Chinese Taipei, Japan. Weakest performers: Turkey, UAE, Malta.

Dimension 2 separates stronger performers on TIMMS vs PISA: strongest performers on TIMMS relative to PISA are in order: Turkey, Korea, Russia, Hungary, United Arab Emirates, while strongest performers on PISA relative to TIMMS are: New Zealand, Canada, Australia, Norway, Italy. The five most balanced countries in the tradeoff are roughly: Slovenia, England, Hong Kong, Japan, USA.

Overperformance in TIMSS relative to PISA can arguably be used as a proxy for schooling quality, since it’s more dependent on academic/curricular skills than on raw intelligence. I am not surprised by the good figures for Korea, Russia, and to a lesser extent, the rest of East Asia and the post-Communist world. However, the UAE and Turkey are surprising.

Dimension 3 separates out Science nations vs Math nations: Most heavily Science vs Math: Slovenia, England, USA, New Zealand, Turkey and most heavily Math vs Science: Hong Kong, Malta, Korea, Italy, Norway.

As much as including TIMMS might be a worse proxy of “IQ” than just PISA, I have included in the above graphic a measure of using the PC1 overall performance score to convert to IQ, based on the assumption that England is 100 and Japan 104.3 as in your PISA conversion. There’s a bit of swing, not too much, compared to PISA alone.

m then extended his analysis to encompass Reading, which is unsurprisingly “less correlated with the other measures”:


as well as to the PIAAC Survey of Adult Skills:



Singapore’s the biggest relative loser when the skills measure is rolled in as well, with the least advantage on PIAAC skills relative to TIMMS / PISA. Most other countries gain compared to the other PCA, as they are more advantaged relative to England and the East Asians on young people’s life skills than they are on young people’s education measures.

• Category: Race/Ethnicity • Tags: PISA, Psychometrics, Statistics 





There were problems with data collection in Argentina, Kazakhstan, and Malaysia, so their results must be treated with caution.

Furthermore: “Because the results of Kazakhstan in 2015 are based only on multiple-choice items, they cannot be reliably compared to the results of other countries, nor to Kazakhstan’s results in previous assessments” (pp. 81 of the report).

Data for China was drawn from four provinces: Beijing, Shanghai, Jiangsu, and Guangdong. Since the first three of these are known to be cognitive clusters, they are not perfectly representative of China. For further discussion go here: PISA 2015 Released: China Disappoints.


Country Math Reading Science Mean “IQ”
Singapore 564 535 556 551.7 107.8
Hong Kong (China) 548 527 523 532.7 104.9
Japan 532 516 538 528.7 104.3
Macao (China) 544 509 529 527.3 104.1
Estonia 520 519 534 524.3 103.7
Canada 516 527 528 523.7 103.6
Chinese Taipei 542 497 532 523.7 103.6
Finland 511 526 531 522.7 103.4
Korea 524 517 516 519.0 102.9
B-S-J-G (China) 531 494 518 514.3 102.2
Ireland 504 521 503 509.3 101.4
Slovenia 510 505 513 509.3 101.4
Germany 506 509 509 508.0 101.2
Netherlands 512 503 509 508.0 101.2
Switzerland 521 492 506 506.3 101.0
New Zealand 495 509 513 505.7 100.9
Denmark 511 500 502 504.3 100.7
Norway 502 513 498 504.3 100.7
Poland 504 506 501 503.7 100.6
Belgium 507 499 502 502.7 100.4
Australia 494 503 510 502.3 100.4
Viet Nam 495 487 525 502.3 100.4
United Kingdom 492 498 509 499.7 100.0
Portugal 492 498 501 497.0 99.6
France 493 499 495 495.7 99.4
Sweden 494 500 493 495.7 99.4
Austria 497 485 495 492.3 98.9
Russia 494 495 487 492.0 98.8
Spain 486 496 493 491.7 98.8
Czech Republic 492 487 493 490.7 98.6
United States 470 497 496 487.7 98.2
Latvia 482 488 490 486.7 98.0
Italy 490 485 481 485.3 97.8
Luxembourg 486 481 483 483.3 97.5
Iceland 488 482 473 481.0 97.2
Croatia 464 487 475 475.3 96.3
Lithuania 478 472 475 475.0 96.3
Hungary 477 470 477 474.7 96.2
Israel 470 479 467 472.0 95.8
Argentina (CABA) 456 475 475 468.7 95.3
Malta 479 447 465 463.7 94.6
Slovak Republic 475 453 461 463.0 94.5
Greece 454 467 455 458.7 93.8
Kazakhstan 460 427 456 447.7 92.2
Chile 423 459 447 443.0 91.5
Malaysia 446 431 443 440.0 91.0
Bulgaria 441 432 446 439.7 91.0
Cyprus 437 443 433 437.7 90.7
Romania 444 434 435 437.7 90.7
United Arab Emirates 427 434 437 432.7 89.9
Uruguay 418 437 435 430.0 89.5
Turkey 420 428 425 424.3 88.7
Trinidad and Tobago 417 427 425 423.0 88.5
Argentina 409 425 432 422.0 88.3
Moldova 420 416 428 421.3 88.2
Montenegro 418 427 411 418.7 87.8
Mexico 408 423 416 415.7 87.4
Costa Rica 400 427 420 415.7 87.4
Albania 413 405 427 415.0 87.3
Thailand 415 409 421 415.0 87.3
Colombia 390 425 416 410.3 86.6
Qatar 402 402 418 407.3 86.1
Georgia 404 401 411 405.3 85.8
Jordan 380 408 409 399.0 84.9
Indonesia 386 397 403 395.3 84.3
Brazil 377 407 401 395.0 84.3
Peru 387 398 397 394.0 84.1
Lebanon 396 347 386 376.3 81.5
Tunisia 367 361 386 371.3 80.7
FYROM 371 352 384 369.0 80.4
Kosovo 362 347 378 362.3 79.4
Algeria 360 350 376 362.0 79.3
Dominican Republic 328 358 332 339.3 75.9
OECD Average 490 493 493 492.0 98.8
• Category: Race/Ethnicity • Tags: Map, PISA, Psychometrics 

Here is the download link:


First Impressions

(1) China B-S-J-G (Beijing-Shanghai-Jiangsu-Guangdong) has a PISA-equivalent national IQ of 102. This is actually worse than the IQ=103 leaked 2009 results based on 12 provinces, which I posted about a few years ago. Even more curiously, Beijing, Shanghai, and Jiangsu all constitute three of the top five Chinese provinces based on other IQ tests (original), with Guangdong in 7th place; the provinces China uses for PISA are still evidently selected for their likelihood of doing very well. Furthermore, coverage was an unimpressive 64% of the population.

UPDATE: A better source cited by commenter Bobbi based on Raven tests shows Guangdong getting 2 IQ points less than the Chinese average, so this would partially cancel out the inclusion of three otherwise cognitive elite provinces.

(2) Vietnam gets a national IQ of 100, although at 49% based on even smaller coverage than China’s. This, too, was a decline from PISA 2012, when they got around 102. Korea also dropped substantially from 106 in 2012 to 103 this round. All in all – a bad beat for “Team East Asia.”

(3) Russia improved significantly, which went from 96 in 2009 to 97 in 2012 and 99 this year – and this is with 95% coverage. This is likely because the generation that grew up in the 1990s was afflicted by the consequences of the Soviet collapse and shock therapy, which included a near halving of meat consumption and an alcoholism epidemic (education spending also fell, but performance on these tests seems to be pretty inelastic to this factor). But the 2015 PISA cohort was born around 2000, when living standards began to recover along with nutritional diversity and all kinds of other biodemographic indicators. Note that I did expect this to happen: “… in the next decade I expect the Flynn Effect to kick off in Russia’s favor, raising its average IQ levels to their theoretical peak of 100 by the 2020′s.

(4) Poland does not repeat its anomalously good IQ=103 results from 2012, converging down to a still respectable 101.

(5) The US modestly improves to 98.

(6) A major improvement for Argentina, which raised its IQ to 95 by an amazing 10 IQ points. This improvement is so big that questions have to be asked as to how exactly they managed it. It wasn’t because they dropped their commendable habit, first noticed by Steve Sailer, of rounding up their dimmest 15 year olds to take the PISA tests (unlike Mexico, or Vietnam); to the contrary, they continued going well beyond the call of duty, achieving 104% coverage – the highest of any country.

UPDATE: From Sailer’s thread, Gaucho de la Pampa comments:

1) Argentina no longer means Argentina, it’s just the city of Buenos Aires (CABA – Ciudad Autónoma de Buenos Aires) . The results for the rest of the country were invalidated because of cheating:

2) It’s not about rounding up missing schoolchildren, if that many went missing from taking the test the results would be annulled as they were in Argentina, rather in some countries vast numbers of 15 year olds don’t attend school and PISA is a test designed for those attending school.

3) The glass half full interpretation is that as Mexico’s share of 15 year olds that attend school has increased its scores have remained roughly static (though obviously crappy)

LOL, well that explains everything. Good job Argentina!

(7) At the very bottom of the list, the Dominican Republic has a PISA-equivalent IQ of 76, which is roughly equivalent to that of India (which, incidentally, dropped out of PISA 2015, possibly on account of doing so badly in the last assessment). Lynn estimates it at 82. According to an analysis by Jason Malloy, Cuba gets an average of 90 on Raven’s tests, and 105-109 (!) from a couple of UNESCO comparative regional tests. So it’s probably safe to say that Cuba is cognitively better off than the Dominican Republic, which makes its decline from double its income level in the 1950s to 2/3 of it today all the more attributable to central planning.

• Category: Race/Ethnicity • Tags: China, PISA, Psychometrics, Russia 

This year half of the top 10 best performing universities in the global ACM-International Collegiate Programming Competition were Russian.

Place Name Solved Time Last solved
1 St. Petersburg State University 11 1560 290
2 Shanghai Jiao Tong University 11 1567 272
3 Harvard University 10 1358 269
4 Moscow Institute of Physics & Technology 10 1437 281
5 University of Warsaw 10 1586 278
6 Massachusetts Institute of Technology 9 1021 247
7 St. Petersburg ITMO University 9 1026 208
8 Ural Federal University 9 1167 212
9 University of Wroclaw 9 1193 252
10 Nizhny Novgorod State University 9 1222 292

This isn’t a fluke; Russia does incredibly well in these programming competitions. Since 2000, Russia has won 11 out of 17 years, including the past five years consecutively. The only other winners during this period have been China (four times) and Poland (twice). Ex-commie bloc stronk.

It’s probably not a matter of superior intelligence. Most estimates put Russia’s average IQ at around 97 and I don’t disagree with that.

So presumably it’s significantly a function of (1) motivation and/or (2) superior education.

Regarding motivation, that’s probably significantly higher in the ex-commie bloc. A computer science major from MIT or UC Berkeley is almost guaranteed a high five digit salary upon graduation. A Russian (or a Pole, etc) is not; not only are salaries lower across the economy, but if anything their domestic markets for STEM majors are oversaturated. So they have a lot of incentives to try to stand out and increase their chances of getting a job offer from an American or West European firm. Consequently, they likely take such competitions more seriously.

Regarding education, it is quite possible Russia and Eastern Europe have an advantage in this sphere as well, despite the poor showings of their universities in most international rankings. Russians do relatively poorly on the PISA tests, which feature problems commonly found in everyday life and have heavier g loadings, but in contrast they do very well on the TIMSS tests, which are far more “academic” in format and less heavily g loaded. These is in fact a lot of anecdotal evidence that Russian mathematical pedagogy is better than American. For winning math and programming competitions (if not building successful companies, which require a wider and more general range of talents) this sort of skew in cognitive abilities is probably optimal.

• Category: Race/Ethnicity • Tags: Programming, Psychometrics, Russia 

Commentator jimmyriddle finds statistics about the ethnic composition of scientific cadres in the Soviet Union in 1973 via Cassad (the original comes via the blogger Burkino Faso).



Drawing on earlier statistical data, although on a more limited sample of different ethnicities, we have the following sets of correlations:

  • 1926 Census, literacy amongst 50 years olds+ – r = .92
  • 1926 Census, overall literacy – r = .72
  • 1939 Census, overall literacy – r = .61
  • 1939 Census, high school graduation – r = .93
  • 1939 Census, higher education – r = .99

Considering this without Jews who are huge outliers everywhere here:

  • 1926 Census, literacy amongst 50 years olds+ – r = .82
  • 1926 Census, overall literacy – r = .74
  • 1939 Census, overall literacy – r = .72
  • 1939 Census, high school graduation – r = .91
  • 1939 Census, higher education – r = .93

So the two best predictors are:

(1) The literacy rate amongst the last Tsarist era generation, i.e. people who were 50+ years old in 1926, hence were born before 1876. That was before the advent of mass schooling in the Russian Empire, so I suspect that was when the literacy rate amongst the various regions of the Russian Empire was also the most “g loaded” (apart from places where the Protestant factor was also at play).

(2) Even more so, the share of people with higher education according to the 1939 Census. This stands to reason.


PISA suggests that the Georgians have very low IQs. I mean literally India-like, in the low 80s. However, the above suggests that its underperformance is more a result of massive brain drain – as in other countries that score ridiculously lower than expected based on their ethnic composition, such as Moldova and Puerto Rico, and before the 1990s, Ireland – as well as possibly the collapse of the schooling system to an extent that didn’t happen elsewhere. Probably the two most highly achieving Georgians today are historical detective fiction writer and political oppositioner Boris Akunin (Chkhartishvili) and the controversial but undoutedbly very talented Moscow based sculptor Zurab Tsereteli.

Armenia does not participate in PISA, but its results from TIMSS were significantly lower than Russia’s, at around Ukraine’s or Romania’s level. However, it might be grossly underperforming for the same reasons that Georgia is. First off, a massive amount of the brainier Armenians have emigrated to Russia and the West. In both places they are prominent relative to their numbers, with a powerful lobby in the US (even if it has nothing on the Jewish lobby) and a very powerful lobby in Russia that one could argue stretches all the way to Sergey Lavrov himself, who is half-Armenian. Former chess champion and oppositionist Gary Kasparov is half-Armenian, while the older Soviet chess champion Tigran Petrosian was fully Armenian. They are also the closest cousins of the Jews in terms of genetic distance. A mischievous observation one can make is that like the Jews, Armenians also seem to be unduly prone to political radicalism when abroad, from Sergey Kurginyan and Gary Kasparov (in their own ways) in Russia to Maoist nutjob Bob Avakian and SJW figurehead Anita Sarkeesian in the US, but maintain a safely homogenous and culturally rightist (if dumber) society at home.

In the overall scheme of things, from Jews down to Gypsies, there are no really big surprises.


I came across this map of German performance in math, biology, physics, and chemistry in the IQB-Ländervergleich 2012, a test they hold once every few years in conjunction with PISA.


With the sole exception of Berlin, which is close to rock bottom, the former GDR states along with Bavaria were consistently at the top of the ratings. 50-60 points difference correspond to two years’ worth of learning progress.

Saxony, home of Pegida and known in the Cold War as the “valley of the clueless” because its specific geography hampered Western radio and TV broadcasts, is at the very top.


This is confirmed by the regional PISA results for 2009.

What could possibly explain this?


Who could have imagined?

In reality, East Germans are nothing special academically; they are about mid-range compared to the average ethnic German elsewhere in Germany.


The key difference is that East Germans had yet to be really enriched back when these tests were carried out. The map above shows the percentage of immigrants in the German districts as of 2011.

On a historical note, it’s possible that the roots of the South German – that is, Bavaria and Baden-Wuerttemberg – dominance on the German cognitive scoreboard are pretty old.



Thirty years after the printing press first appeared in Europe, you could already begin to discern three distinct clusters of concentration – Northern Italy, the Low Countries, and South Germany. (The first two, of course, were famous for their respective Renaissances). Back then, there was no independent Protestant pro-literacy effect, so we might expect to see a considerable correlation across Catholic Europe between literacy rates and IQ (though back then climatic factors would had a much bigger influence in suppressing literacy rates in the colder, less urbanized areas of Northern Europe). And it is reasonably to suppose that there was likewise a good correlation between literacy rates and the adoption of the printing press.

Furthermore, unlike the Low Countries and Italy, South Germany is a hilly inland area, an environment that tends to depress IQ (iodine deficiency – the European alpine areas used to be known for having many cases of goitre and cretinism), so their achievement in quickly accumulating such a high density of printing presses nonetheless must have already hinted at a very respectable genotypic IQ.

I seem to recall reading in National Literacy Campaigns and Movements, as in Sweden, there were ecclesiastical reglaments making marriage more difficult for illiterate people in southern Germany from the 18th century. If so this would have been a eugenic policy that helped maintain or increase further those high IQ levels, though the effect would have been attenuated by the Bavarians having one of Europe’s highest illegitimacy rates (something like 27% IIRC).

• Category: Race/Ethnicity • Tags: Germany, Immigration, Psychometrics 

Prolific IQ researcher Richard Lynn together with two Russian collaborators have recently published arguing that multiple aspects of socio-economic development – infant mortality, fertility, stature, and literacy-as-a-proxy for intelligence were significantly intercorrelated in late Tsarist Russia.


Literate rate of the European part of the Russian Empire in 1897.

Here is the link to the paper – Regional differences in intelligence, infant mortality, stature and fertility in European Russia in the late nineteenth century

And here is a summary by James Thompson – 50 Russian oblasts.

To the right: Here’s your map, JayMan. You’re welcome.

The main potential sticking point:

There are no data for regional intelligence in the nineteenth century and we have therefore adopted rates of literacy as a proxy for intelligence. This is justified on the grounds that a high correlation between literacy rates and intelligence have been reported in a number of studies. For example, a correlation of .861 between literacy rates for Italian regions in 1880 and early twenty-first century IQs has been reported by Lynn (2010); a correlation of .83 between literacy rates for Spanish regions in the early twenty-first century has been reported by Lynn (2010); (Lynn, 2012); and a correlation of 0.56 between literacy rates and IQs for the states and union territories of India in 2011 has been reported by Lynn and Yadav (2015). There is additional support for using literacy in the nineteenth century as a proxy for intelligence in the results of a study by Grigoriev, Lapteva and Ushakov (Григорьев, Лаптева, Ушаков, 2015) showing a correlation of .58 between literacy rates of the peasant populations of the districts (uezds) of the Moscow province in 1883 and the results of the Unified State Exam and State Certification on Russian Language in the districts of the contemporary Moscow oblast.

The methodology at first struck me as being rather problematic.

I’ve read a bit about Russian state literacy programs in the 19th century (National Literacy Campaigns and Movements) and one of their main features is that they tended to spread out from the central European Russian provinces due to cost effectiveness reasons, hence the low literacy rates of e.g. Siberia in Lynn’s data set. However, there is no particular evidence that Siberian Russians are any duller than average Russians. To the contrary, some 3% of Siberian schoolchildren become “Olympians” – high performers who qualify for highly subsidized higher education. This proportion is lower than the 15% of the central region (which hosts Moscow, Russia’s main cognitive cluster with a 107 average IQ), and the 14% of the north-west region (which hosts Russia’s second cognitive cluster with a 103 average IQ Saint-Petersburg, plus the Russians there are probably slightly brighter in general on account of Finno-Ugric admixture), but is considerably higher than in any other Russian Federal District: The Urals and Volga (both about 2%), and the Far Eastern, Southern, and Caucasus (all considerably below 1%).

In other words, would such a historical literacy – modern intelligence correlation apply to Russia as it does to Italy, Spain, and to a lesser extent, India?


Average 2009 PISA results by Russian region.

Fortunately, we don’t have to postulate, since we do actually have PISA data for many Russian provinces that I revealed back in 2012.

This allows us to test if Lynn’s assumptions apply.

There are difficulties, to be sure. Not all Russian provinces were tested in PISA, and there is, needless to say, no data for any of the Ukrainian and Polish oblasts, or for Belarus. As such, only 20 Russian provinces could be tested in this manner (26 if you also include now independent countries excluding Russia itself).

In some cases, names have changed, typically to honor some faceless Soviet bureaucrat; in more problematic cases, borders have changed significantly (e.g. the five provinces of Estonia, Livonia, Courland, Kovno, and Vilna have become the three countries of Estonia, Latvia, and Lithuania – I have tried to average the literacy figures between them in a common sense but back of the envelope way). The Moscow Governorate has been split into the City of Moscow (with its 107 average IQ) and Moscow oblast (with a modest 96 average IQ). Which of those should be attached to Moscow’s 1897 literacy rate of 40%? (As it happens, I went with just the City of Moscow instead of figuring out how to weigh the populations and adjust and so forth. I’m not trying to writea formal paper, after all).


There is an exponential correlation of R=0.75 between average PISA derived IQs of Russian regions and of now independent countries, and their literacy rate according to the 1897 Census. Therefore, this bears out Lynn’s assumptions.

The two downwards outliers – more relatively intelligent than literate – are Moscow, Tatarstan, Tula, Samara, and Tambov. Moscow is easily explainable – the city itself in Tsarist times would have been more literate than the Moscow Governorate, while its average IQ was artificially boosted in Soviet times since it became not just the empire’s political but also its cognitive (artistic, scientific) capital. Getting a Moscow propiska required considerable intelligence.

The three very major upwards outliers – more relatively literate than intelligent – are the Finno-Ugric Baltic states: Finland, Estonia, and Latvia. This can’t have been a non-Orthodox/Muslim thing: Both Poland (On-The-Vistula Governorate) and Lithuania (Kovno and Vilna) lie neatly on the correlation curve. Nor was it something Finno-Ugric; Karelia (then Olonets) is not an exception either. It must have been something specific just to them and the most obvious explanation is Protestantism. There is a lot of literature on the independent literacy-raising effects of Protestantism and I see no reasons why Estonia, Latvia, and Finland should have been exceptions to that.

Another outlier, though this one is at the bottom of the IQ scale, is Moldova. To be fair I think Moldova’s PISA-derived IQ is artificially lowered by a third to half of an S.D. due to the massive brain drain it has experienced after the collapse of the Soviet Union (something like half the working age population are Gastarbeiters in the EU and Russia). We see similar drops in other countries so afflicted, such as (possibly) Puerto Rico, and (almost certainly) Ireland during most of the 20th century, when it repeatedly reported IQs in the ~90 range (and ironically one of the reasons Richard Lynn himself abandoned it to move to Northern Ireland, thus getting stuck in the most depressed region of the UK and missing out on the rise of the Celtic Tiger a few years later).


The correlation improves further to R=0.80 when we consider only those Tsarist-era provinces which are still part of the Russian Federation. This is accomplished (more than) entirely just by removing the Protestant Baltic nations (Finland, Estonia, and Latvia) and Moldova (whose current day average IQ is depressed due to massive brain drain as per above).

As usual Lynn does his north/south IQ gradient analysis, finding it to be a real thing but diminishing to nothing once the Baltic states of Estonia, Livonia, and Courland are accounted for.

Quoting from Thompson’s summary:

The Russian provinces differed significantly by geographical location. The positive correlations with latitude (r= .33, p<.05) and the negative correlation with longitude (r=−.43, p<.01) show that the rates of literacy were higher in the northand west than in the south and east. These trends were partly determined by the rates of literacy being highest in the north-western provinces of St. Petersburg and the three Baltic states of Estland, Livland and Kourland (correspondingapproximately but not precisely to contemporary Estonia and Latvia; Livland consisted of southern part of contemporary Estonia and eastern part of contemporary Latvia). Removing these four regions makes both correlations non-significant (.21 and −.23).


The Pale of Settlement in 1897.

One additional issue worth bearing in mind: The influence of the Jews. Namely, their concentration in the Pale of Settlement, which correlates to modern day Poland, Belarus, and right-bank Ukraine (west of the Dnieper). There were more than 5.2 million Jews, and their literacy rates were very high (according to the 1926 Soviet Census, Jews over the age of 50 – i.e., who had been educated under the Empire – had a literacy rate of 63% versus 28% for ethnic Russians).

This must have “artificially” raised the literacy rates in this area – as pertains to those regions’ 21st century average IQs, anyway, since the vast majority of those Jews are no longer there due to the trifecta of the Holocaust, Jackson-Vanik, and Aliyah. The effect would probably be to reduce the “indigenous” literacy rates in Lithuania and Poland closer to those of European Russia, while pushing the already low literacy rates of strongly ethnic Malorossiyan and Belorussian provinces considerably lower still. Not a single province of modern Ukraine outside historical Novorossiya (with its strong Great Russian admixture) had a literacy rate above 20% in 1897, despite highly literate Jews helping them out with the statistics.

Unfortunately, there is a severe paucity of usable psychometric data from Ukraine – for instance, it is one of the very few European countries that doesn’t participate in PISA. So its average IQ has to be estimated through generally more indirect means. It does the converted equivalent of 9 IQ points worse than Russia on the TIMSS standardized test. Ukrainians spend less than half as much time as Russians reading, and those from the western parts at least spend a lot more time participating in torchlit processions and chanting “Putin Khuylo.” Some of those activities are considerably more g loaded than others. The low literacy rates in late Tsarist Malorossiya, coupled with the finding of a close correlation between those literacy rates and modern day average IQ across both Russian provinces and today’s independent post-Soviet states, constitutes further evidence of a modest average IQ in Ukraine. Higher than in Moldova to be sure, but probably closer to the level of the Balkans than to Poland.


Sources: Grigoriev, Lapteva, and Lynn 2015; Karlin 2012 (derived from PISA 2009).

IQ Literacy in 1897
Astrakhan 94.8 15.5%
Bashkortostan 93.4 16.7%
ESTONIA 102.1 77.9%
FINLAND 106.6 75.6%
Kaluga 91.7 19.4%
Karelia 98.1 25.3%
Kursk 94.6 16.3%
LATVIA 98.0 74.3%
LITHUANIA 99.0 35.4%
MOLDOVA 84.9 15.6%
Moscow 106.6 40.2%
N. Novgorod 93.1 22.0%
Orenburg 92.7 20.4%
Perm 93.3 19.2%
POLAND 100.2 30.5%
RUSSIA 96.0 21.1%
Ryazan 94.7 20.3%
Saint-Petersburg 102.6 51.5%
Samara 99.2 22.1%
Saratov 96.0 23.8%
Tambov 95.9 16.6%
Tatarstan 98.1 17.9%
Tula 98.6 20.7%
Ulyanovsk 91.5 15.6%
Vladimir 98.9 27.0%
Vologda 95.3 19.1%
Voronezh 92.7 16.3%

Literacy and Social Development in 1890s Russia (from Grigoriev et al. 2015)

Incidentally, I am not surprised to see Yaroslavl being the top non-Baltic/non-capital Russian region by literacy rate in 1897. It struck me as by far the cleanest and most civilized provincial Russian town on the Golden Ring when I visited it in 2002 (a time when Russia was still shaking off the hangover of the Soviet collapse). Curiously enough, it also hosted one of the most vigorous insurrections against the Bolshevik regime in central Russia. Although it was not one of the regions covered by PISA, I would not be surprised if Yaroslavl oblast was to get a 100-102 score on it should it be carried out there (and as would be implied by the correlation curve).



Leonid Bershidsky is a democratic journalist who immigrated to Germany from Russia when Putin triggered him one too many times in 2014. Most of his articles deal with Eastern Europe in general and the Eternal Collapse of Russia under Putin in specific (though to be fair he is far from the worst Russia journalist out there). He also regularly makes space on his Bloomberg blog for promoting various other fashionably progressive causes, which in the light of recent events is predictably dominated by immigration and open borders.

Open borders for Europe and especially Germany, anyway. He does not think the Gulf states like Saudi Arabia have to take in refugees because it would dilute the per capita value of their oil wealth and create the “potential for political, ethnic and sectarian tension.” Mass enrichment is a a joy and a blessing that only European countries are worthy of partaking in. Rape? What rape? All Putinist lies!

In short, he is a highly representative and articulate voice of the transatlantic globalist elites.

Last week, I was drawn into a debate with him due to a ReTweet of one of his

This is the main reason I have for preserving the “debate” I had on IQ and immigration with him last week on Twitter. Though every bit as tedious as you probably imagine it, it is useful to be reminded every so often of how utterly and willfully uninformed conventional elite opinion remains on these issues down to the banal recycling of the Steve Jobs argument.

Note in particular the struggles of poor Garett Jones (he of the Hive Mind) to communicate basic psychometric findings to Bershidsky while avoiding saying anything that could potentially get him fired.

Before clicking on the image below to enlarge, note that this is a fairly big file (2.5MB).


Feel free to continue this “debate” in the comments section.

• Category: Race/Ethnicity • Tags: Elites, Immigration, Psychometrics, Trolling 
HBD, Hive Minds, and H+

Today is the publication date of Hive Mind, a book by economist Garett Jones on the intimate relationship between average national IQs and national success, first and foremost in the field of economics.

I do intend to read and review it ASAP, but first some preliminary comments.

This is a topic I have been writing about since I started blogging in 2008 (and indeed well before I came across Steve Sailer or even HBD) and as it so happens, I have long been intending to write a similar sort of book myself – tentatively titled Apollo’s Ascent – but one that focuses more on the historical aspect of the relationship between psychometrics and development:

My basic thesis is that the rate of technological progress, as well as its geographical pattern, is highly dependent on the absolute numbers of literate high IQ people.

To make use of the intense interest that will inevitably flare up around these topics in the next few days – not to mention that rather more self-interested reason of confirming originality on the off chance that any of Garett Jones’ ideas happen to substantively overlap with mine – I have decided to informally lay out the theoretical basis for Apollo’s Ascent right now.

1. Nous

Assume that the intellectual output of an average IQ (=100, S.D.=15) young adult Briton in the year 2000 – as good an encapsulation of the “Greenwich mean” of intelligence as any – is equivalent to one nous (1 ν).

This can be used to calculate the aggregate mindpower (M) in a country.

Since sufficiently differing degrees of intelligence can translate into qualitative differences – for instance, no amount of 55 IQ people will be able to solve a calculus problem – we also need to be able to denote mindpower that is above some threshold of intelligence. So in this post, the aggregate mindpower of a country that is above 130 will be written as M(+2.0), i.e. that aggregate mindpower that is two standard deviations above the Greenwich mean.

2. Intelligence and Industrial Economies

There is a wealth of evidence implying an exponential relationship between average IQ and income and wealth in the United States.


Click to enlarge.

There is likewise a wealth of evidence – from Lynn, Rindermann, La Griffe du Lion, your humble servant, etc. – that shows an exponential relationship between levels of average national IQ and GDP per capita (PPP adjusted). When you throw out countries with a legacy of Communism and the ruinous central planning they practiced (China, the Ex-USSR and Eastern Europe, etc), and countries benefitting disproportionately from a resource windfall (Saudi Arabia, the UAE, etc), there is an amazing R2=0.84 correlation between performance in the PISA international standardized student tests and GDP (PPP) per capita. (In sociology, anything about R2=0.3 is a good result).

The reasons for this might be the case are quite intuitive. At the most basic level, intelligent people can get things done better and more quickly. In sufficiently dull societies, certain things can’t get done at all. To loosely borrow an example from Gregory Clark’s A Farewell to Alms, assume a relatively simple widget that requires ten manufacturing steps that have to be done just right to make it commercially viable. Say an 85 IQ laborer has a failure rate of 5% for any one step, while a 100 IQ laborer has a failure rate of 1%. This does not sound like that big or cardinal of a difference. But repeated ten times, some 40% of the duller worker’s production ends up being a dud, compared to only 10% of the brighter worker’s. Consequently, one is competitive on the global markets, whereas the other is not (if labor costs are equal; hence, of course, they are not).

Now imagine said widget is an automobile, with hundreds of thousands of components. Or an aircraft carrier, or a spaceship. Or a complex surgery operation.

More technical way of looking at this: Consider the GDP equation, Y = A * K^α * L^(1-α), in which K is capital, L is labour, α is a constant that usually equals about 0.3, and A is total factor productivity. It follows that the only way to grow per capita output in the longterm is to raise productivity. Productivity in turn is a function of technology and how effectively it is utilized and that in turn depends critically on things like human capital. Without an adequate IQ base, you cannot accumulate much in the way of human capital.

There are at least two further ways in which brighter societies improve their relative fortunes over and above what might merely be implied by their mere productivity advantage at any technological level.


Source: Swiss Miss.

First, capital gets drawn to more productive countries, until the point at which its marginal productivity equalizes with that of less productive countries, with their MUCH LOWER levels of capital intensity. First World economies like Germany, Japan, and the US are extremely capital intensive. It is probably not an accident that Japan, Korea, and Taiwan – some of the very brightest countries on international IQ comparisons – also have by far the world’s highest concentrations of industrial robots per worker (and China is fast catching up). Since economic output is a function not only of pure productivity but also of capital (though subject to diminishing returns) this provides a big further boost to rich countries above the levels implied by their raw productivity. And as the age of automation approaches, these trends will only intensify.

Second, countries with higher IQs also tend to be better governed, and to effectively provide social amenities such as adequate nutrition and education to their populations. Not only does it further raise their national IQs, but it also means that it is easier to make longterm investments there and to use their existing human capital to its full potential.

All this implies that different levels of intelligence have varying economic values on the global market. At this stage I am not so much interested in establishing it with exactitude as illustrating the general pattern, which goes something like this:

  • Average IQ = 70 – Per capita GDP of ~$4,000 in the more optimally governed countries of this class, such as Ghana (note however that many countries in this class are not yet fully done with their Malthusian transitions, which will depress their per capita output somewhat – see below).
  • Average IQ = 85 – Per capita GDP of ~$16,000 in the more optimally governed countries of this class, such as Brazil.
  • Average IQ = 100 Per capita GDP of ~45,000 in the more optimally governed countries of this class, or approximately the level of core EU/US/Japan.
  • Average IQ = 107 – Per capita GDP of potentially $80,000, as in Singapore (and it doesn’t seem to have even finished growing rapidly yet). Similar figures for elite/financial EU cities (e.g. Frankfurt, Milan) and US cities (e.g. San Francisco, Seattle, Boston).
  • Average IQ = 115 – Largely a theoretical construct, but that might be the sort of average IQ you’d get in, say, Inner London – the center of the global investment banking industry. The GDP per capita there is a cool $152,000.

Countries with bigger than normal “smart fractions” (the US, India, Israel) tend to have a bigger GDP per capita than what could be assumed from just from their average national IQ. This stands to reason because a group of people equally split between 85 IQers and 115 IQers will have higher cognitive potential than a room composed of an equivalent number of 100 IQers. Countries with high average IQs but smaller than normal S.D.’s, such as Finland, have a slightly smaller GDP per capita that what you might expect just from average national IQs.

These numbers add up, so a reasonable relationship equilibrium GDP (assuming no big shocks, good policies, etc) and the structure and size of national IQ would be:

Equilibrium GDP of a country exponent (IQ) * the IQ distribution (usually a bell curve shaped Gaussian) * population size * the technological level

Which can be simplified to:

Y ≈ c*M*T

… where M is aggregate mindpower (see above), T is the technology level, and c is a constant denoting the general regulatory/business climate (close to 1 in many well run capitalist states, <0.5 under central planning, etc).

To what extent if any would this model apply to pre-industrial economies?

3. Intelligence and Malthusian Economies


Source: A Farewell to Alms

Very little. The problem with Malthusian economies is that, as per the old man himself, population increases geometrically while crop yields increase linearly; before long, the increasing population eats up all the surpluses and reaches a sordid equilibrium in which births equal deaths (since there were a lot of births, that means a lot of deaths).

Under such conditions, even though technology might grow slowly from century to century, it is generally expressed not in increasing per capita consumption, but in rising population densities. And over centennial timescales, the effects of this (meager) technological growth can be easily swamped by changes in social structure, biome productivity, and climatic fluctuations (e.g. 17th C France = pre Black Death France in terms of population, because it was Little Ice Age vs. Medieval Warm Period), or unexpected improvements in agricultural productivity e.g. from the importation of new crops (e.g. the coming of sweet potatoes to China which enabled it to double its population over the previous record even though it was in outright social regress for a substantial fraction of this time).

All this makes tallying the rate of technological advance based on population density highly problematic. Therefore it has to be measured primarily in terms of eminent figures, inventions, and great works.


Distribution of significant figures across time and place. Source: Human Accomplishment.

The social scientist Charles Murray in Human Accomplishment has suggested a plausible and objective way of doing it, based on tallying the eminence of historical figures in culture and the sciences as measured by their prevalence in big reference works. Societies that are at any one time intensively pushing the technological frontiers outwards are likely to be generating plenty of “Great People,” to borrow a term from the Civilization strategy games.

To what extent does the model used for economic success apply to technology?

4. Intelligence and Technology Before 1800

A narrow intellectual elite is responsible for 99%+ of new scientific discoveries. This implies that unlike the case with an economy at large, where peasants and truck drivers make real contributions, you need to have a certain (high) threshold level of IQ to materially contribute to technological and scientific progress today.

The Anne Roe study of very eminent scientists in 1952 – almost Nobel worthy, but not quite – found that they averaged a verbal IQ of 166, a spatial IQ of 137, and a math IQ of 154. Adjusted modestly down – because the Flynn Effect has only had a very modest impact on non-rule dependent domains like verbal IQ – and you get an average verbal IQ of maybe 160 (in Greenwich terms). These were the sorts of elite people pushing progress in science 50 years ago.

To really understand 1950s era math and physics, I guesstimate that you would need an IQ of ~130+, i.e. your typical STEM grad student or Ivy League undergrad. This suggests that there is a 2 S.D. difference between the typical intellectual level needed to master something as opposed to making fundamental new discoveries in it.

Moreover, progress becomes steadily harder over time; disciplines splinter (see the disappearance of polymath “Renaissance men”), and eventually, discoveries become increasingly unattainable to sole individuals (see the steady growth in numbers of paper coauthors and shared Nobel Prizes in the 20th century). In other words, these IQ discovery thresholds are themselves a function of the technological level. To make progress up the tech tree, you need to first climb up there.

An extreme example today would be the work 0f Japanese mathematician Shinichi Mochizuki. At least Grigory Perelman’s proof of the Poincare Conjecture was eventually confirmed by other mathematicians after a lag of several years. But Mochizuki is so far ahead of everyone else in his particular field of Inter-universal Teichmüller theory that nobody any longer quite knows whether he is a universal genius or a lunatic.

In math, I would guesstimate roughly the following set of thresholds:

Mastery Discovery
Intuit Pythagoras Theorem (Ancient Egypt) 90 120
Prove Pythagoras Theorem (Early Ancient Greece) 100 130
Renaissance Math (~1550) 110 140
Differential Calculus (~1650+) 120 150
Mid-20th Century Math (1950s) 130 160
Prove Poincare Conjecture (2003) 140 170
Inter-universal Teichmüller theory (?) 150 180

This all suggests that countries which attain new records in aggregate elite mindpower relative to their predecessors can very quickly generate vast reams of new scientific discoveries and technological achievements.

Moreover, this elite mindpower has to be literate. Because a human brain can only store so much information, societies without literacy are unable to move forwards much beyond Neolithic levels, their IQ levels regardless.

As such, a tentative equation for estimating a historical society’s capacity to generate scientific and technological growth would look something like this:

Technological growth c * M(>threshold IQ for new discovery) * literacy rate


ΔT c * M(>discovery-threshold) * l

in which only that part of the aggregate mindpower that is above the threshold is considered; c is a constant that illustrates a society’s propensity for generating technological growth in the first place and can encompass social and cultural factors, such as no big wars, no totalitarian regimes, creativity, etc. as well as technological increases that can have a (generally marginal) effect on scientific productivity, like reading glasses in Renaissance Italy (well covered by David Landes), and the Internet in recent decades; and the literacy rate l is an estimate of the percentage of the cognitive elites that are literate (it can be expected to generally be a function of the overall literacy rate and to always be much higher).

Is it possible to estimate historical M and literacy with any degree of rigor?


Source: Gregory Clark.

I think so. In regards to literacy, this is an extensive area of research, with some good estimates for Ancient Greece and the Roman Empire (see Ancient Literacy by William Harris) and much better estimates for Europe after 1500 based on techniques like age heaping and book production records.

One critical consideration is that not all writing systems are equally suited for the spread of functional literacy. For instance, China was historically one of the most schooled societies, but its literacy tended to be domain specific, the classic example being “fish literacy” – a fishmonger’s son who knew the characters for different fish, but had no hope of adeptly employing his very limited literacy for making scientific advances, or even reading “self-help” pamphlets on how to be more effective in his profession (such as were becoming prevalent in England as early as the 17th century). The Chinese writing system, whether it arose from QWERTY reasons or even genetic reasons – and which became prevalent throughout East Asia – surely hampered the creative potential of East Asians.

Estimating average national IQs historically – from which M can be derived in conjunction with historical population sizes, of which we now generally have fairly good ideas about – is far more tricky and speculative, but not totally hopeless, because nowadays we know the main factors behind national differences in IQ.

Some of the most important ones include:

  • Cold Winters Theory – Northern peoples developed higher IQs (see Lynn, Rushton).
  • Agriculture – Societies that developed agriculture got a huge boost to their IQs (as well as higher S.D.s).
  • Inbreeding – Can be estimated from rates of consanguineous marriage, runs of homozygosity, and predominant family types (nuclear? communitarian?), which in turn can be established from cultural and literary evidence.
  • Eugenics – In advanced agricultural societies, where social relations come to be dominated by markets. See Greg Clark on England, and Ron Unz on China.
  • Nutrition – Obviously plays a HUGE role in the Flynn Effect. Can be proxied by body measurements, and fortunately there is a whole field of study devoted to precisely this: Auxology. Burials, conscription records, etc. all provide a wealth of evidence.
  • Parasite Load – Most severe in low-lying, swampy areas like West Africa and the Ganges Delta.

This old comment of mine to a post by Sailer is a demonstration of the sort of reasoning I tend to employ in Apollo’s Ascent.

All this means that educated guesses at the historic IQs of various societies are now perfectly feasible, if subject to a high degree of uncertainty. In fact, I have already done many such estimates while planning out Apollo’s Ascent. I will not release these figures at this time because they are highly preliminary, and lacking space to further elucidate my methods, I do not want discussions in the comments to latch on to some one figure or another and make a big deal out of it. Let us save this for later.

But in broad terms – and very happily for my thesis – these relations DO tend to hold historically.

Classical Greece was almost certainly the first society to attain something resembling craftsman level literacy rates (~10%). Ancient Greeks were also unusually tall (indicating good nutrition, for a preindustrial society), lived in stem/authoritarian family systems, and actively bred out during their period of greatness. They produced the greatest scientific and cultural explosion up to that date anywhere in the world, but evidently didn’t have quite the demographic weight – there were no more than 10 million Greeks scattered across the Mediterranean at peak – to sustain it.

In 15th century Europe, literacy once again begun soaring in Italy, to beyond Roman levels, and – surely helped by the good nutrition levels following the Black Death – helped usher in the Renaissance. In the 17th century, the center of gravity shifted towards Anglo-Germanic Europe in the wake of the Reformation with its obsession with literacy, and would stay there ever after.

As regards other civilizations…

The Islamic Golden Age was eventually cut short more by the increasing inbreeding than by the severe but ultimately temporary shock from the Mongol invasions. India was too depressed by the caste system and by parasitic load to ever be a first rate intellectual power, although the caste system also ensured a stream of occasional geniuses, especially in the more abstract areas like math and philosophy. China and Japan might have had an innate IQ advantage over Europeans – albeit one that was quite modest in the most critical area, verbal IQ – but they were too severely hampered by labour-heavy agricultural systems and a very ineffective writing system.

In contrast, The Europeans, fed on meat and mead, had some of the best nutrition and lowest parasitic load indicators amongst any advanced civilization, and even as rising population pressure began to impinge on those advantages by the 17th-18th centuries, they had already burst far ahead in literacy, and intellectual predominance was now theirs to lose.

5. Intelligence and Technology under Industrialism

After 1800, the world globalized intellectually. This was totally unprecedented. There had certainly been preludes to it, e.g. in the Jesuit missions to Qing China. But these were very much exceptional cases. Even in the 18th century, for instance, European and Japanese mathematicians worked on (and solved) many of the same problems independently.


Source: Human Accomplishment.

But in the following two centuries, this picture of independent intellectual traditions – shining most brightly in Europe by at least an order of magnitude, to be sure, but still diverse on the global level – was to be homogenized. European science became the only science that mattered, as laggard civilizations throughout the rest of the world were to soon discover to their sorrow in the form of percussion rifles and ironclad warships. And by “Europe,” that mostly meant the “Hajnal” core of the continent: France, Germany, the UK, Scandinavia, and Northern Italy.

And what had previously been but a big gap became an awning chasm.

(1) In the 19th century, the populations of European countries grew, and the advanced ones attained universal literacy or as good as made no difference. Aggregate mindpower (M) exploded, and kept well ahead of the advancing threshold IQ needed to make new discoveries.

(2) From 1890-1970, there was a second revolution, in nutrition and epidemiology – average heights increased by 10cm+, and the prevalence of debilitating infectitious diseases was reduced to almost zero – that raised IQ by as much as a standard deviation across the industrialized world. The chasm widened further.

(3) During this period, the straggling civilizations – far from making any novel contributions of their own – devoted most of their meager intellectual resources to merely coming to grips with Western developments.

This was as true – and consequential – in culture and social sciences as it was in science and technology; the Russian philosopher Nikolay Trubetzkoy described this traumatic process very eloquently in The Struggle Between Europe and Mankind. What was true even for “semi-peripheral” Russia was doubly true for China.

In science and technology, once the rest of the world had come to terms with Western dominance and the new era of the nation-state, the focus was on catchup, not innovation.This is because for developing countries, it is much more useful in terms of marginal returns to invest their cognitive energies into copying, stealing, and/or adapting existing technology to catch up to the West than to develop unique technology of their own. Arguments about, say, China’s supposed lack of ability to innovate are completely besides the point. At this stage of its development, even now, copying is much easier than creating!

This means that at this stage of global history, a country’s contribution to technological growth isn’t only a matter of the size of its smart fractions above the technological discovery IQ threshold. (This remains unchanged: E.g., note that a country like Germany remains MUCH more innovative per capita than, say, Greece, even though their aveage national IQs differ by a mere 5 points or so. Why? Because since we’re looking only at the far right tails of the bell curve, even minor differences in averages translate to big differences in innovation-generating smart fractions).

It also relates closely to its level of development. Countries that are far away from the technological frontier today are better served by using their research dollars and cognitive elites to catch up as opposed to inventing new stuff. This is confirmed by real life evidence: A very big percentage of world spending on fundamental research since WW2 has been carried out in the US. It was low in the USSR, and negligible in countries like Japan until recently. Or in China today.

Bearing this in mind, the technological growth equation today (and since 1800, more or less) – now due to its global character better described as innovation potential – would be better approximated by something like this:

Innovation potential ≈ c * M(>threshold IQ for new discovery) * literacy rate * (GDP/GDP[potential])^x


I c * M(>discovery-threshold) * l * (Y/Y[P])^x

in which the first three terms are as before (though literacy = 100% virtually everywhere now), and potential GDP is the GDP this country would obtain were its technological endowment to be increased to the maximum level possible as dictated by its cognitive profile. The “x” is a further constant that is bigger than 1 to reflect the idea that catchup only ceases to be the most useful strategy once a country has come very close to convergence or has completely converged.

Japan has won a third of all its Nobel Prizes before 2000; another third in the 2000s; and the last third in the 2010s. Its scientific achievements, in other words, are finally beginning to catch up with its famously high IQ levels. Why did it take so long?

Somebody like JayMan would say its because the Japanese are clannish or something like that. Other psychometrists like Kenya Kura would notice that perhaps they are far less creative than Westerners (this I think has a measure of truth to it). But the main “purely IQ” reasons are pretty much good enough by themselves:

  • The Nobel Prize is typically recognized with a ~25-30 year lag nowadays.
  • It is taking ever longer amounts of time to work up to a Nobel Prize because ever greater amounts of information and methods have to be mastered before original creative work can begin. (This is one consequence of the rising threshold discovery IQ frontier).
  • Critically, Japan in the 1950s was still something of a Third World country, with the attended insults upon average IQ. It is entirely possible that elderly Japanese are duller than their American counterparts, and perhaps even many Europeans of that age, meaning smaller smart fractions from the Nobel Prize winning age groups.

Japan only became an unambiguously developed country in the 1970s.

And it just so happens that precisely 40 years after this did it begin to see a big and still accelerating increase in the numbers of Nobel Prizes accruing to it!

Extending this to South Korea and Taiwan, both of which lagged around 20 years behind Japan, we can only expect to see an explosion in Nobel Prizes for them from the 2020s, regardless of how wildly their teenagers currently top out the PISA rankings.

Extending this to China, which lags around 20 years behind South Korea, and we can expect to see it start gobbling up Nobel Prizes by 2040, or maybe 2050, considering the ongoing widening of the time gap between discovery and recognition. However, due to its massive population – ten times as large as Japan’s – once China does emerge as a major scientific leader, it will do so in a very big way that will rival or even displace the US from its current position of absolute primacy.

As of 2014, China already publishes almost as many scientific papers per year as does the US, and has an outright lead in major STEM fields such as Math, Physics, Chemistry, and Computer Science. (Though to be sure, their quality is much lower, and a significant fraction of them are outright “catching up” or “adaption” style papers with no new findings).

If we assume that x=1, and that c is equal for both China and the US, then it implies that both countries currently have broadly equal innovation potential. But of course c is not quite equal between them – it is lower for China, because its system is obviously less conductive to scientific research than the American – and x is higher than 1, so in practice China’s innovation potential is still considerably lower than that of the US (maybe a quarter or a third). Nonetheless, as China continues to convege, c is going to trend towards the US level, and the GDP gap is going to narrow; plus it may also be able to eke out some further increases in its national average IQ from the current ~103 (as proxied by PISA in 2009) to South Korea’s level of ~107 as it becomes a truly First World country.

And by mid-century it will likely translate into a strong challenge to American scientific preeminence.

6. Future Consequences

The entry of China onto the world intellectual stage (if the model above is more or less correct) will be portentuous, but ultimately it will in its effects on aggregate mindpower be nowhere near the magnitude in global terms of the expansion in the numbers of literate, mostly European high IQ people from 1450 to 1900, nor the vast rise in First World IQ levels from 1890-1970 due to the Flynn Effect.

Moreover, even this may be counteracted by the dysgenic effects already making themselves felt in the US and Western Europe due to Idiocracy-resembling breeding patterns and 80 IQ Third World immigration.

And no need for pesky implants!

Radically raise IQ. And no need for pesky neural implants!

A lot of the techno-optimistic rhetoric you encounter around transhumanist circles is founded on the idea that observed exponential trends in technology – most concisely encapsulated by Moore’s Law – are somehow self-sustaining, though the precise reasons why never seem to be clearly explained. But non-IT technological growth peaked in the 1950s-70s, and has declined since; and as a matter of fact, Moore’s Law has also ground to a halt in the past 2 years. Will we be rescued by a new paradigm? Maybe. But new paradigms take mindpower to generate, and the rate of increase in global mindpower has almost certainly peaked. This is not a good omen.

Speaking of the technological singularity, it is entirely possible that the mindpower discovery threshold for constructing a superintelligence is in fact far higher than we currently have or are likely to ever have short of a global eugenics program (and so Nick Bostrom can sleep in peace).

On the other hand, there are two technologies that combined may decisively tip the balance: CRISPR-Cas9, and the discovery of the genes for general intelligence. Their maturation and potential mating may become feasible as early as 2025.

While there are very good reasons – e.g., on the basis of animal breeding experiments – for doubting Steve Hsu’s claims that genetically corrected designer babies will have IQs beyond that of any living human today, increases on the order of 4-5 S.D.’s are entirely possible. If even a small fraction of a major country like China adopts it – say, 10% of the population – then that will in two decades start to produce an explosion in aggregate global elite mindpower that will soon come to rival or even eclipse the Renaissance or the Enlightenment in the size and scope of their effects on the world.

The global balance of power would be shifted beyond recognition, and truly transformational – indeed, transhuman – possibilities will genuinely open up.


Chanda Chisala’s article on black/white IQ differences has been making quite the stir in the HBDsphere. It is well worth reading in its entirety, as some of the points he makes – e.g., the evidence for high IQ amongst certain African ethnic groups such as the Igbo – are quite compelling and novel even to those well versed in this debate. But the central plank of his argument is ultimately a strike against the “hereditarian position” in IQ on the basis that the children of African immigrants are failing to regress to the mean.

The predictable response of the hereditarians is to adopt the environmentalist argument of super high immigrant selection to explain this unexpected trend: where some environmentalists propose that these immigrants are the most driven achievers in their countries, the hereditarians say they are the most intellectually elite, the ones from the topmost segment of the IQ bell curve in their countries; the outliers who got some lucky genes in an otherwise poor-gene environment. But like the hyper-driven-personality hypothesis, this argument cannot explain the equally, if not more impressive, achievements of their children: lottery winners never have children who also win the lottery. The stubborn refusal of their children to conspicuously regress to the much lower African genetic mean IQ (and not even to the African American mean IQ) predicted by hereditarians is simply inexplicable under their racial genetic hierarchy.

The problem is that African IQs from all social groups are highly repressed because of Third World factors like malnutrition and parasitic load. Very significantly so – around 15 points, or one standard deviation. When Third Worlders migrate to the First World, they experience a sort of “accelerated Flynn Effect” as their children with one plane ride get to enjoy advantages such as superior nutrition, medicine, etc. that had taken their host countries a century to build up. It’s not so much that regression to the mean isn’t happening but that it is being cancelled out by Flynn. This is a point that with apparently just one exception on the part of the IQ blogger Pumpkin Person has been overlooked in both Chisala’s article and the comments to it.

Let’s do a few back of the envelope calculations based on several plausible scenarios to demonstrate this.

The (commonly accepted) phenotypic IQ of Sub-Saharan Africans is typically estimated at 65-80, with 70 being a particularly common estimate. Their genotypic IQ is around 85 extrapolating from African Americans (there are issues such as ~20% Caucasian admixture, selection effects during slavery, diversity in Africa itself, etc. but let’s keep things simple). As is also well known, and cited by Chisala himself, African immigrants to both the UK and the US tend to be highly credentialed (more credentialed in fact than any other ethnic immigrant group). A reasonable estimate of their average phenotypic IQ would be 100, i.e. two S.D.’s above the Nigerian/Ghanaian/etc. average (three S.D.’s would be too implausible since there are so very few of them), and a genotypic IQ of 115.

Some at this point would object that the genotypic/phenotypic difference diminishes for higher IQ Africans since they’d be wealthier and more “elite” on average than the commoners, and hence have access to better food, medicine, etc. This is a good argument, but actual height data indicates that in the Third World entire populations are shifted down – both commoner and elites – relative to their counterparts in the First World. You can see the same phenomenon not only geographically but historically, e.g. average US Presidential heights, which increased by more than three inches between 1776 and today (and that is despite the US being very well fed by global standards even two centuries ago).

Assume the standard method of calculating offspring IQ: The average of the father’s and mother’s IQs, plus some degree of convergence to the mean of the parents’ racial genotypic IQs, i.e. what is otherwise known as regression to the mean, which is usually estimated at 40%.

Now let’s assume our African immigrant is an economic migrant, i.e. an educated and credentialed Nigerian, as opposed to a semi-literate refugee from wartorn Somalia or DRC. (Average IQ of Black African immigrant offspring in the UK is about 93 according to the CAT tests, as Chisala points out and as I mentioned three years back. Since this group will include a lot of these very low IQ Somali/Eritrean/etc. refugees, the average IQ of children of African economic migrants should logically be a lot higher, i.e. maybe around the White average. This hypothesis will be further supported below).

Let’s assume our African immigrant is male for simplicity’s sake – plus the fact there are somewhat more men than women amongst African immigrants anyway – and that he made some of the following marriage choices:

  • Marries another cognitively elite Black immigrant woman just like himself, i.e. phenotypic IQ of 100, and genotypic IQ of 115, resulting in average offspring IQ of 107, i.e. standard “model minority”-level performance. It would not be particularly surprising or strange if Britain’s best performing secondary student in one particular year – Chidera Ota, prominently featured in Chisala’s article – was to come from the high end of this particular group’s bell curve.
  • Marries a Black immigrant woman whom he married back at home, thus she did not undergo the selection for higher IQ that is the selection process for economic migrants, thus has a phenotypic IQ of 85 and a genotypic IQ of 100. Resultant average IQ of offspring: 101.
  • Marries an African American woman with a phenotypic and genotypic IQ of 100 (i.e. associational mating). Expected offspring IQ: 101.
  • Marries a Caucasian woman with a phenotypic and genotypic IQ of 100 (i.e. associational mating). Expected offspring IQ: 103.

Here’s a summary:

Genotypic IQs F (ego) F (race) M (ego) M (race) S & D
Black immigrant (elite) + Black immigrant (elite) 115 85 115 85 107
Black immigrant (elite) + Black immigrant (nonelite) 115 85 100 85 100.5
Black immigrant (elite) + US Black (assoc) 115 85 100 85 100.5
Black immigrant (elite) + US White (assoc) 115 85 100 100 102.5

So you see the pattern? Cognitively, the children of African immigrants are basically Caucasians, i.e. a standard deviation above African Americans, but nowhere close to an elite cognitive group like Ashkenazi Jews or US Indians who are almost a full S.D. above Caucasians. They will come to form a population group with a fixed cognitive profile set around 100 or slightly higher (since regression to the mean stops after one generation), and as such they will do fairly well socially and economically. Most likely, better then Caucasians, since they will benefit from affirmative action policies in education and employment designed to benefit 1 S.D. duller African Americans while in fact being cognitively similar to Caucasians (think Ashkenazi Jews counting as Whites in university admissions). All of this, in fact, seems to be happening in real life.

Chisala might not have “disproven” the hereditarian or HBD position (at least its nuanced, non-White Nationalist part that pays due respect to auxology and Flynn dynamics). But he did demonstrate that African immigrants are doing fairly well for themselves. Indeed, as a cognitively elite Zambian immigrant, Chisala would presumably be quite the expert on it.

And don’t get me wrong, this is a genuinely attractive message, at least so long as you are an egalitarian blank slatist (US liberals), a cultural supremacist (US conservatives), or even a cognitive elitist who doesn’t attach any value to racial particularism. Liberals can point to them as living proof that Blacks are just as mentally gifted as Whites, and it is structural racism which is keeping African Americans down. As such, there needs to be more affirmative action, more racial quotas, more laws against hate speech, etc. to end it. Conservatives too would welcome it. They will praise the work ethic and family values of these African immigrants, citing the lack thereof amongst African Americans as the real cause of why they lag so much behind other ethnic groups in the US. That in turn will enable them to continue to wage their culture war against genuine African American culture. The economists and economic rationalists will be happy. Surely this is a good reason to expand immigration from Sub-Saharan Africa? More jobs, more skills, more entrepreneurialism. If anything, the only unhappy people would be the White Nationalists, and who cares about those primitive troglodytes anyway?

Even so, it should be pointed out that this argument can be critiqued even from morally universalistic, if still cognitively elitist, principles. An argument could be made that accepting African cognitive elites might improve the host societies, at least in the views of non-nativists: By increasing the size of the middle class, solving skills shortages, and providing fuel for the egalitarian narrative which – whatever its problems with logic, reason, and data – is nonetheless morally superior to “kneejerk” ideologies based on real racism and exclusion.

But proponents of these views should also seriously consider what effect their policies are going to have on the African societies that the high IQ immigrants are abandoning. It is becoming increasingly accepted in development economics that countries with high numbers of “smart fractions” – either via a high average IQ, like China, or at least a substantial “Brahmin” class, like India or South Africa – tend to do much better than low IQ and cognitively homogenous countries, like… most of Sub-Saharan Africa. The region has very few cognitive elites to start off with, and a large percentage of them are getting sucked up into Western societies that frankly have orders of magnitude less need of them than their own cognitively-strapped countries. These losses are not just financial, though those are no small matter even just by themselves: It takes a lot of money to train a doctor or an engineer, money which Sub-Saharan Africa generally doesn’t have. Even worse are the cognitive losses, as the stock of competent administrators and businessmen dwindles, reducing the size of Africa’s smart fractions even further and resulting in even more poverty and dysfunction.

It is adaptive to adopt the language of the Left on this issue. Enabling educated African immigration at a large scale is Western cognitive colonialism against the African continent, and is nothing more than a subtler version of the resource rapine that it subjected Africa to back in the days when imperialism was overt and didn’t bother concealing its iron fist beneath a velvet glove. Colonialism is bad and morally unjustifiable, and all foes of the global plutocratic elites must unite against it.


Why is the HBDsphere so damn interested in IQ, anyway?

While I can’t speak for the “movement” at large, in my own case the interest stems from the fact that it explains so much about our world. (In fact, I was interested in this topic long before I discovered HBD, Charles Murray, Jensen, Lynn, Rushton, etc). In particular, it convincingly answers the central question of political economy since the days of Adam Smith – why are some nations poor and some nations rich? After all the long debates about the merits of free markets over industrial policy, over the influence of institutions versus geography; after all the human miseries suffered from zealous adherence to some ideology or other, from the Great Leap Forwards in China to the capitalist disaster zone that neoliberalism made of the ex-Soviet Union in the 1990s, after all these blunders, mishaps, and occasional horrors committed in search of the Answer, we find that it mostly boils down to just one ultimately rather banal thing: Some peoples are more intelligent than others, work more efficiently, and hence enjoy greater wealth; and as a result of said greater efficiency, capital naturally flows towards them, further multiplying their output relative to the backwards countries.

In extreme cases, institutional factors do make a huge difference. Countries with a socialist (central planning) legacy – that is, East Central Europe, the ex-USSR, China, Vietnam – are still systemically much poorer than countries where markets have long functioned with at least some minimal degree of freedom, even though their IQs do not differ much from those of the US, Western Europe, and Japan. Stress on the “minimal” – beyond some fairly modest point of economic freedom and basic political stability, it appears that institutions and economic openness offer rapidly diminishing returns; for instance, the Belorussian economy, which is still 90% state owned and a dictatorship, was actually the most successful of all the ex-Soviet economies after 1991, including even economic reform stars like Estonia (actually Azerbaijan performed even better, but it was helped by a massive oil windfall). Speaking of which, on the other side of the correlation curve you have countries with a very big resource windfall per capita – Saudi Arabia, South Africa, Norway, etc. – which are much richer than the level “warranted” by the quality of their human capital. But once we take these two groups out of the equation, and also get rid of tiny finance-orientated city-states, the correlation between national IQ and economic wealth becomes extremely close – a fact all the more remarkable when we consider that estimates of both national IQ and GDP per capita (PPP) can vary fairly widely.

Here is a graph I made from 2013, which shows a correlation of R2=0.84. This is entirely in line with other similar calculations by professional psychometricians like Heiner Rindermann.


That said, as I noted even back then, there are some curious outliers in the “capitalist normal” countries. Moreover, these outliers tend to be concentrated at the wealthy frontier: The US is a positive outlier, whereas Japan, the East Asian countries, Finland, and to a lesser extent, the “Anglo offshoots” (Canada, Australia, New Zealand) are negative outliers.

As economic historian pseudoerasmus pointed out on many occasions, while national IQ is central to the growth story for low-income and middle-income countries in catch-up growth, for already developed nations with their standard 100±5 IQs the benefits accrue overwhelmingly to those with more “marginal” advantages, such as those having somewhat better institutions, or conditions for doing business. This is a hypothesis that makes good theoretical sense, but a closer examination reveals that things might not be that simple. The Anglo nations have what are widely regarded as very good institutions, courts, and conditions for business, but they are relative underperformers, even (especially) when productivity is taken into account. Japan has a 5-7 IQ advantage over, say, Italy, but its GDP per capita (PPP) is similar, while its productivity is significantly lower – even though Japan rates higher on ease of business and perception of corruption indices. There must be other factors that are at play, and I will admit that I am unsure as to what they are. But before we get ahead of ourselves, let’s examine the data in greater detail.

This is the data table I used in the charts in this article:


I limited myself to countries that satisfied the following list of conditions:

  • Those that had a substantial population, at least 5 million or more (smaller countries tend to be financial/tourism hubs with too much artificially inflated wealth).
  • Did not have a central planning legacy that depressed their wealth (so, no country from the socialist camp during the Cold War) or a big resource endowment per capita (so, out go countries like Saudi Arabia and Norway). We are talking primarily of the old OECD members minus Mexico and Turkey.
  • Are wealthy, i.e. have a GDP per capita of at least $20,000. We already established that the correlation between national IQ and wealth in poorer countries is very good; the question we now want to answer is why it begins to break down at the edge of the graphs.

GDP per capita is measured in purchasing power parity terms because it better reflects the real level of production and living standards in any country and accounts for short-term currency fluctuations. Productivity is the GDP per capita (PPP) adjusted for the labor participation rate and average hours worked per country, i.e. GDP per hour worked. Most of the data I got from the World Bank or the OECD, though I frequently had to look for other sources in the cases of Taiwan, Hong Kong, and Singapore. The regional averages were calculated as a weighted population average of each regional label. National IQs were derived from the average of the Math, Science, and Reading component in PISA 2009.

The first series of graphs show regional and country national IQ versus GDP per capita (PPP) data, with the bubbles scaled for population size.


Here, at an amalgamated level, we already see a distinct pattern: Americans are much richer than they “should” be, whereas East Asians are much poorer. But curiously, the Anglo offshoots are closer to East Asia here than they are to European-stock populations, so it is not at all obvious that it is an HBD issue.

And now for the country specific data.


While all the countries of Western Europe hew close to the line of best fit, again there are three major exceptions: The US to the upside, and Japan and South Korea to the downside.

The obvious and immediate explanation is that some countries have greater labor participation rates, and/or work more hours. So a natural adjustment would be to calculate the GDP per capita generated per manhour of work and see if that explains American and East Asian exceptionalism relative to Western Europe.

I would note at the outset a few caveats to bear in mind. First, in many cases – certainly regarding the US vs. Western Europe – a large share of the differences in overall labor participation is explained by the greater percentage of American youth and the elderly in the workforce by dint of its less generous welfare state (left-wing view) and less restrictive labor laws (right-wing view). Increasing the labor participation of both of these groups will yield only marginal improvements in total output because they are far less productive than people in their prime. Likewise, working longer hours is of questionable value, because workers will presumably either get more tired and less productive, and/or end up wasting time due to Parkinson’s Law (“work expands so as to fill the time available for its completion”). On paper, Greeks work far longer than Germans… if by “working” you mean drinking coffee. The Japanese have it even worse; extra hours “worked” there means pretending to work until the boss leaves. Germans, on the other hand, actually get all the important stuff done quickly and efficiently, and get to enjoy a big chunk of the rest of the day. Americans tend to work long hours and productively.

Even so, on average, productivity is probably more impacted by national IQ than the level of GDP per capita. At the very least, by far the biggest discrepancy – that between the US and Western Europe – largely vanishes after this adjustment.


Although the gap between the Westerners (barring the Anglo offshots) and East Asia then becomes even wider.


Now that I’ve laid out all the data, time to consider some hypotheses for American exceptionalism and Asian mediocrity. At the outset, I should thank pseudoerasmus and James Thompson for participating in the Twitter discussion where many of these ideas were initially raised, analyzed, and critiqued.

1) Historical Leadership. The US has been at the technological edge since its inception; Britain industrialized a bit earlier, but there was never a significant gap in per capita output. Moreover, it burst clear of everyone else in the wake of World War Two, which devastated most of Europe. But 70 years is more than enough time to recover and catch up. In fact, that is precisely what happened: The first part of the period was of the Wirtschaftswunder, the Trente Glorieuses, Il Sorpasso, the Japanese Miracle, and the East Asian Tigers. But ever since 1990 or thereabouts, longterm per capita growth rates in developed Europe, the US, and Japan – for all the rhetoric about “European stagnation” and “Japan’s lost decade” – have basically converged. Here is Paul Krugman’s famous chart on this:


The only two major countries for which uncompleted convergence could still be a significant factor are South Korea and perhaps Taiwan. But any further relative gains on their parts, if the past five years are anything to go by, are going to be slow and marginal. For all its dazzling PISA performance and blisteringly rapid economic catchup, Korea’s productivity levels are still equivalent to those of Portugal, which has traditionally been the poorest country in Europe with the exception of a few Balkan backwaters, and Greece, which is at the tail end of a multi-year depression. Both Portugal and Greece have national IQs almost 10 points below Korea’s.

2) Immigration, Population Composition, and IQ Structure. But if anything, this makes the puzzle even more acute. We know that in recent decades Europe received a lot of immigrants, whose IQs are far lower than those of the natives and show no signs of convergence. The US, meanwhile, is host to two major population groups – Blacks and Non-White Hispanics – with consistently subpar IQs that together make up more than 20% of the population. If anything, that should depress productivity, which probably partially explains New Zealand, where ~90 IQ Maoris and Pacific Islanders also make up slightly more than 20% of the population. In contrast, high IQ and ethnically homogenous Japan, Korea, and Finland all underperform, as do Canada and Australia, which are not ethnically homogenous but do make sure to have cognitively elitist immigration policies.

That said, there are two reasons why this effect might not be all that powerful for both Europe and the US. First of all, in both Europe and the US, these NAMs (Non-Asian Minorities) have a relatively greater demographic preponderance amongst the youngest cohorts, whose members are either not in the workforce at all (infants, schoolchildren, students) or aren’t able to contribute much anyway (they are younger workers with less experience; while they might be quicker on the uptake, older workers often beat them with experience, especially in the more cognitively intense professions). This will likely do Europe and the US no good in the longterm, as they develop ever larger, ethnically distinct cognitive/economic underclasses that will pull down overall GDP per capita and productivity, but this probably just doesn’t play that big of a role… for now.

Moreover, at least in the US, the situation is further improved by the presence of sizable “smart fractions,” which have a disproportionately large positive effect on overall GDP per capita according to many psychometricians like Heiner Rindermann. These smart fractions are both ethnic – most notably, the 2% of the population that is Jewish – as well as the result of a global cognitive clustering effect (many of the world’s brightest and most ambitious people are inordinately drawn to US universities and Silicon Valley). It would also explain Israel’s overperformance – while the national IQ is depressed by Arabs and Sephardic Jews, and the economy is burdened by Haredi welfare bums, the Ashkenazi Jewish cognitive elite still manages to compensate for all that and elevate GDP per capita above the global correlation curve.

Some thinkers have speculated that the reason for East Asian underperformance is that although they have higher IQs than Whites, they have fewer very high IQ people (“smart fractions”) because of narrower distributions. The only problem with this very plausible and reasonable theory is that it is almost certainly completely wrong. The PISA tests show that East Asian S.D.’s are no different from those of European countries (though Finland’s, curiously enough, is lower at a statistically significant level). This theory could furthermore be disproved by a cursory glance at a list of names of members of the US Mathematical Olympiad teams – since 2010, fully 75% have either Chinese or Vietnamese last names.

Another, more plausible theory, advanced by Griffe de Lion as well as Rindermann, is that some forms of IQ, most notably verbal, in which the European-East Asian gap is very modest or even non-existent, are relatively more important for economic success than mathematical aptitude, where the gap is substantial, or visuospatial ability, where it is as big as 10 points. (Lynn actually claims that Europeans are verbally smarter, but PISA shows otherwise, though it does confirm that the Asian/European gap in verbal IQ is much less than the mathematical one). This would largely though not fully resolve the puzzle of East Asian underperformance, though you would still have to convincingly explain why verbal IQ in particular is more important for economic prosperity than, say, just g.

Finally, we must also bear in mind that gaps in cognitive ability can increase or decrease with age. Most tests of intelligence are performed on children or teenagers because it is easy to get big, representative samples from them. But what is true for under-18s may no longer be true for the mid-25s, when fluid intelligence is maximized (the ability to learn), or the 50s, when crystallized intelligence (total stock of applicable knowledge and experience) is maximized. For instance, while male and female IQ tends to be similar, though the latter have famously narrower distributions, it appears that at least on progressive matrices tests, a 5 point gap opens up during the 20s in favor of men and persists thereafter. Just as a significant part of the Flynn Effect can be explained through faster maturation due to better nutrition and parasitic disease control during the past century, so the biological reality that men fully physically mature about five years later than women could explain the appearance of a gender IQ gap in adulthood. Could there be similar processes at work in regards to different ethnic groups? Certainly it seems to pertain to the famous Black-White IQ gap, which increases with age, and very substantially so. Note that productivity in most smart fraction professions peaks in the 50s, when crystallized intelligence is maximized.

Could it be that the Asian IQ lead over Europeans in childhood and adolescence closes or even reverses with age? I have no idea. I was unable to find any hard statistical data on this. (Do tell me in the comments if you have). So for now it must remain but a stab in the dark hypothesis. However, if this is indeed the case – that the Caucasian/Asian IQ gap diminishes or even reverses with age, or put another way, that the much maligned “old white man” really is the smartest dude around – would be able to fully explain Asian underperformance, especially if paired with the observations on the relatively greater importance of verbal IQ as it pertains to economic prosperity.

3) Institutions and Economic Freedom. We know that in the most extreme cases – for instance, central planning under Communist regimes – lack of economic freedom leads to substantially inferior economic outcomes relative to what they might have been under market conditions. Beyond some minimal level, however, the role that increasing economic freedom plays seems to be subject to rapidly diminishing returns. Chile is one of the freest economies on the planet thanks to Señor Pinochet, Argentina is the exact opposite – but their GDP per capita is virtually the same, as – who’d have guessed it? – are their national IQs. But Chile and Argentina are middle-income countries, so institutional differences might not be making themselves felt as much as in fully developed countries.

So let’s look at the biggest outliers and the quality of their instutitions and business environment, as proxied by the World Bank’s Ease of Doing Business indicator and Transparency International’s Corruption Perceptions Index.


Now this is hardly a rigorous statistical test, but it’s clear that there’s little or no evident connection. All negative outliers are well within the world’s top quintile by ease of doing business – unlike, say, Italy (56th) and Greece (61st), which although poor by OECD standards are not however major outliers on the IQ charts. Finland, Australia, New Zealand, and Canada are some of the freest economies and best places for business on the planet.

The only two negative outliers which might have a significant problem with corruption are Taiwan and Korea. Now Taiwan is… a strange case. According to one poll, also carried out by Transparency International, 36% (!) of them said they paid a bribe in the past year. This is almost certainly a statistical fluke. On the other hand, only 2% of Koreans said they paid a bribe in the past year; only Denmark, the UK, and Norway, all countries that everyone agrees have minimal levels of everyday corruption, claimed to have paid fewer bribes. Assuming they weren’t lying, perhaps Korea’s rating on the CPI is overly pessimistic. Regardless – that’s still a lot better than most of the rest of the world, including rich non-outlier countries like Italy and Greece, both of whom are joint 69th on the CPI rankings.

4) Economies of Scale. The US is a single integrated market of more than 300 million people with a common language and set of laws and institutions, which enables massive economies of scale. To a lesser extent, this is also the case in the EU, which now has common markets but is still divided by political-fiscal barriers that are make life very difficult for at least some of their members, such as Greece and the Mediterranean countries generally. While Japan might not be of continental proportions, it does have a very substantial population – at 127 million, it is more than one and a half times as big as Germany’s – so it should enjoy most of the benefits from this as well. This factor would have a negative effect on Australia and especially New Zealand, which have low populations themselves and are geographically distant from other big markets.

5) Geography. The US has some of the best geography for industrial civilization on the entire planet: Multiple excellent ports on both seaboards,and the massive Mississippi River and Great Lakes water network that interconnects the entirety of its central core at next to no cost. Europe has middling geography, while Japan’s is poor and prone to natural disasters. Australia and New Zealand are very isolated, making economies of scale unrealistic. That said, the role of geographic factors in our days of dirt cheap oceanic bulk transport and dense railway networks is presumably quite modest.

6) Resource Windfalls. I purposefully excluded those countries where the economy is very clearly radically inflated by large resource windfalls per capita, such as Norway, but even so this factor is still significant for Canada, where natural resource rents as a share of GDP is at 4.4%, and Australia, where it is 8.0%. Combined with their relatively high national IQs and careful immigration policies, their “underperformance” becomes more puzzling, if anything. Even though the US also has a very substantial resource endowment, its effect is swamped by the overall size of its economy; natural resource rents as a share of GDP are a mere 1.3%.

7) Financial Windfalls. Might be a factor in Singapore’s good (relative to the rest of East Asia) performance. Why not Hong Kong? Because after it rejoined its motherland, China had no particular reason to favor it over, say, Shanghai or Guangdong, and quite a lot of disincentives to, considering the pro-Western tilt of many of Hong Kong’s elites. Singapore, however, was free to continue its project of becoming the world’s third major financial hub after London and New York, and its skyhigh GDP per capita (though unremarkable productivity) is a result of that. However, as mentioned at the start, I purposefully excluded places that were so small that a financial or tourism sector could play a dominant role, such as Luxembourg, Monaco, and Liechtenstein, all of which have ridiculously inflated GDP per capitas. Once you get to a British scale, let alone an American one, the impact of global financial centers like London or New York on GDP per capita becomes swamped by the overall economy.

8) American Alpha. Artificially lower risk premiums in the US means foreigners are willing to “irrationally” invest in American bonds at rates well beyond equilibrium. Here is Willem Buiter’s explanation of this phenomenon:

Some of the excess returns on US investment abroad relative to foreign investment in the US may have reflected true alpha, that is, true US alpha – excess risk-adjusted returns on investment in the US, permitting the US to offer lower financial pecuniary risk-adjusted rates of return, because, somehow, the US offered foreign investors unique liquidity, security and safety. Because of its unique position as the world’s largest economy, the world’s one remaining military and political superpower (since the demise of the Soviet Union in 1991) and the world’s joint-leading financial centre (with the City of London), the US could offer foreign investors lousy US returns on their investments in the US, without causing them to take their money and run. This is the “dark matter” explanation proposed by Hausmann and Sturzenegger for the “alpha” earned by the US on its (negative) net foreign investment position. If such was the case (a doubtful proposition at best, in my view), that time is definitely gone. …

There is no chance that a nation as reputationally scarred and maimed as the US is today could extract any true “alpha” from foreign investors for the next 25 years or so. So the US will have to start to pay a normal market price for the net resources it borrows from abroad. It will therefore have to start to generate primary surpluses, on average, for the indefinite future. A nation with credibility as regards its commitment to meeting its obligations could afford to delay the onset of the period of pain. It could borrow more from abroad today, because foreign creditors and investors are confident that, in due course, the country would be willing and able to generate the (correspondingly larger) future primary external surpluses required to service its external obligations. I don’t believe the US has either the external credibility or the goodwill capital any longer to ask, Oliver Twist-like, for a little more leeway, a little more latitude. I believe that markets – both the private players and the large public players managing the foreign exchange reserves of the PRC, Hong Kong, Taiwan, Singapore, the Gulf states, Japan and other nations – will make this clear.

Such a painful adjustment is indeed what has been occuring in Mediterranean Europe. But note that his pessimistic and falsifiable predictions specifically in regards to the US – that there would be “a global dumping of US dollar assets, including US government assets” – have yet to happen.

9) Cheaper Land and Energy Inputs. Land in the US tends to be pretty cheap, outside the North-East, the SF Bay Area, and a few other prestige locations. Much cheaper than in developed Europe or in Japan. Energy inputs are also lower, specifically in relation to fuel, which is taxed at much lower rates than in Europe or Japan. This should lower the cost of business across the board and increase overall thoroughput.


The only problem? The countries right next to the US here are Canada, Australia, and Japan – some of the biggest negative outliers.

10) Hedonics and GDP Fiddling. There are various claims that the US is really… generous at calculating its GDP. Perhaps “American exceptionalism” is just a statistical artifact? I haven’t studied national accounting practices on any detailed level, though pseudoerasmus has and he is skeptical, and I’m also a bit put off that a lot of the sites that make these claims tend to be libertarian goldbugs and LaRouche types. That said, I will admit to an intuitive sense that there might be something behind this. As the commentator Lazy Glossophiliac has pointed out a few times, many things that are either free or cheap in Europe and most of the rest of the world can be pretty damn expensive in the US. The healthcare industry is just the most blatant (and perhaps grotesque) example, accounting for a prodigal share of American GDP while delivering population health outcomes that are, in general, nothing to write home about. Americans dine out much more frequently than Europeans – the labor of chefs and waiters appears in GDP, while creating a home cooked meal does not. You can probably extend this to quite a lot of different things.

American Exceptionalism, East Asian Mediocrity

To sum up: At the technological edge of high IQ/high wealth per capita, there appears an interesting and puzzling disjoint between the US, which is a big positive outlier, and Japan and the rest of East Asia, which are big negative outliers. Adjusting for labor participation and hours worked, to get in effect a measure of productivity, largely resolves “American exceptionalism” relative to developed Western Europe, but if anything widens the chasm between the West and East Asia even further. Moreover, Australia, Canada, and New Zealand – all Anglo-derived settler societies that are culturally close to the US and enjoy low corruption and good institutions – are moderate negative outliers.

In general, possible explanations are either critically flawed in some way, or only partially explain some difference while deepening the puzzle around some other difference. For instance, cheaper energy inputs might appear to partially explain why the US is a positive outlier, but then it would make the question of why Canada and Australia are negative outliers – even though their fuel taxes are also low – all the more inscrutable. Beyond some fairly minimal conditions like having free markets, the quality of institutions do not appear to play any significant role.

Still, it is possible to identify a few factors that likely play some important role:

1) Economies of Scale – Clearly give the US and to a lesser extent, continental Europe, a boost. Many of the negative non-East Asian outliers are relatively isolated island nations with small populations, especially Australia and New Zealand.

2) Smart Fractions and the US – The two biggest rich positive outliers, the US and Israel, have many duller ethnic minorities but also enjoy an Ashkenazi Jewish cognitive elite. Moreover, a significant percentage of the world’s smartest and most ambitious people immigrates to the US.

3) Personality, Culture, IQ Structure – Apart from the partial exception of Singapore – a fact that is mitigated by its status as a financial city-state – all East Asian states economically underperform relative to where they “should” be at. This is The (Other) East Asian Exception. This leads me to believe that the cause of this must be something that is culturally or even biologically common to the region. Maybe it has something to do with a relative lack of creativity in terms of personality (in Nobel Prizes per capita, as in GDP per capita, Japan far more closely resembles Italy than Germany; while Korea has yet to win a single real, i.e. non-Peace, Prize); maybe it is a consequence of East Asia’s shame culture, which is more socially stultifying than Europe’s guilt culture, and can lead to inefficiencies like paying undue respect to an incompetent boss who just happens to be older; maybe it is simply that East Asian IQ is simply “worth” about 5 points less than European IQ due to its particular quirks or structure (specifically, the fact of the Asian advantage in verbal IQ being much more relatively modest relative to Whites); and/or maybe – and this is by far the most tentative hypothesis here – it might be that the East Asian IQ advantage over Europeans disappears in adulthood, meaning that Europeans still retain a relative preponderance in the fraction of smart 40-50-60 year olds who are responsible for most of the greatest scientific and cultural accomplishments.

4) Other Factors – This leaves only Finland and Canada to explain. Finland’s underperformance might be due to the lower S.D. of its national IQ, if the PISA tests are accurate. Moreover, Richard Lynn pegs Finnish IQ at a standard British 100. Perhaps, for whatever reason, Finns simply perform unduly well on PISA. If Lynn is correct, it would not even be an outlier. Or it could be their particular psychological profile, which might be unfavorable for the expression of ingenuity. Canada could be a modest negative outlier because it borders the US and loses too big a percentage of its smartest fractions to its giant southern neighbor.

• Category: Economics, Science • Tags: Economic Theory, IQ, Psychometrics, Race/IQ 

In a new paper at the (conveniently open) journal The Winnower (h/t @whyvert), building on his earlier work, geneticist Davide Piffer has tried to calculate the genotypic IQs of various world populations, and how they compare to measured phenotypic IQ:

Piffer, David – Estimating the genotypic intelligence of populations and assessing the impact of socioeconomic factors and migrations.

Here is the abstract:

Factor analysis of allele frequencies was used to identify signals of polygenic selection on human intelligence. Four SNPs which reached genome-wide significance in previous meta-analyses were used. Allele frequencies for 26 population were obtained from 1000 Genomes. The resulting factor scores were highly correlated to average national IQ (r=0.92). A regression of IQs on genetic factor scores of developed countries was used to estimate the predicted genotypic IQs of developing countries. The residuals (difference between predicted and actual scores) were negatively correlated to per capita GDP and Human Development Index, implying that countries with low socioeconomic conditions have not yet reached their full intellectual potential.

As far I can see, the methodology is sound (perhaps apart from a few quibbles over phenotypic IQ sources). But this is exceedingly minor, and doesn’t really change anything in a material way. So I will focus here mostly on the real world impacts these findings would imply.

As one might expect, there is a gap – usually a very significant one – between calculated genotypic and measured phenotypic IQ in developing countries. This is only logical, since developing countries frequently suffer from a variety of maladies, such as malnutrition and parasitic disease load, that are almost entirely absent in the First World. These maladies have a negative impact on IQ. (To a very large extent this also explains the Flynn Effect of secular rises in IQ in the developed world. Effectively, developing nations may be considered as living in the the First World’s past).

Not good for IQ.

Not good for IQ.

Below is a table showing measured IQ in developed countries and predicted IQ from the paper.

IQ developed countries Predicted (G.wich) IQ
Vietnam 105.9
HanChineseBejing 105 104.3
HanChineseSouth 105 103.6
Japanese 105 103
Chinese Dai 102.7
British 100 100
UtahWhites 99 99.3
Finns 101 99
Spanish 97 98.1
TuscanItaly 99 97.9
Gujarati Ind. Tx 97.1
Mexican LA 95.1
Indian Telegu UK 95
Punjabi Pakistan 94.9
Puerto Rican 93.5
Colombian 92.5
Bengali Banglade 91.4
Peruvian 91
SriLankanUK 88.7
US Blacks 85 84
Mende Sierra Leo 83.7
Afr.Car.Barbados 83.6
Esan Nigeria 82.1
Gambian 82.1
Yoruba 82
Luhya Kenya 81.4

And here is another table, displaying, for peoples in developing nations, predicted IQ (relative to the standard “Greenwich mean” of 100 for the UK); 100 in the UK); the difference between the predicted and the measured IQ; and GDP per capita in purchasing power terms. They are arranged in order of the size of the phenotypic/genotypic difference.

Predicted (G.wich) IQ “Pseudoresiduals” (Predicted minus measured IQ) GDP per capita PPP (2010-2013) HDI (2012)
Gambian 82.1 20.1 1613 0.438
Mende Sierra Leo 83.7 19.7 1432 0.368
Esan Nigeria 82.1 11.1 5303 0.5
Yoruba 82 11 5303 0.5
Punjabi Pakistan 94.9 10.9 4353 0.535
Bengali Banglade 91.4 10.4 2679 0.554
Puerto Rican 93.5 10 34183
SriLankanUK 88.7 9.7 0.745
Colombian 92.5 9 11540 0.708
Luhya Kenya 81.4 7.4 2626 0.531
Mexican LA 95.1 7.1 15813 0.755
Vietnam 105.9 6.5 4851 0.635
Peruvian 91 6 10756 0.734
Afr.Car.Barbados 83.6 0.6 15324
HanChineseBejing 104.3 -0.7 10485 0.715
HanChineseSouth 103.6 -1.4 10485 0.715
Gujarati Ind. Tx 97.1
Indian Telegu UK 95

Some observations we can consequently make:

Africa: The biggest gaps are all in West Africa. Not only is the region grindingly poor, but it also has perhaps the world’s most acute parasitic disease load, thanks to the hot, humid equatorial climate and low-lying, swampy geography (which the region’s disorganized and resource-pool governments are unable to mitigate) . The gap is lower in Kenya, which as a hilly country can be expected to have a lower parasitic disease load, and non-existent amongst Afro-Caribbean Barbadians, who live in a relatively prosperous country (likely in large part thanks to its “smart fraction”) with one of the most salubrious climates on the planet. On average, it appears that their phenotypic IQ is ~high 60s and their genotypic IQ is ~low 80s. US Black IQ is given as 85, but bear in mind that they have 20% admixture with Caucasoids. (Though on the other hand, US Blacks do slightly better according to PISA, at ~88. If this figure is substituted for in the calculations, then the genotypic estimate for Africans would also rise, though not by very much). Either way, there is thus very substantial room for improvement, but even were that to happen, the overall outlook for self-sustained African convergence to developed world living standards would remain grim.

Latin America: Has a phenotypic IQ of ~mid 80s and genotypic IQ of ~low 90s. As expected, the gap is smaller than in Africa or India (Latin American countries are after all far more socially developed than in West Africa or India, albeit one should should treat straight GDP per capita figures with caution due to the massive levels of inequality). In the developed US, it is basically non-existent, what with Latinos scoring ~low 90s in the PISA tests. The big gap seen in Puerto Rico is intriguing, considering that its close economic ties with the US has allowed it to have a very high GDP per capita relative to its IQ, so lack of money can’t be a limiting factor. But in general, Latin America is already pretty much “where it should be” in terms of prosperity as implied by its level of human capital.

South Asia: Has a phenotypic IQ of ~low 80s and genotypic IQ of ~low to mid 90s. The gap is much bigger than for Latin America, – indeed, comparable to West Africa’s – which is perhaps explainable by dint of India’s greater parasitic disease load, high rates of malnutrition (which is perhaps even higher than in Sub-Saharan Africa), and, in the case of the Punjabis and Bengalis, a strong tradition of FBD marriage, which has very strong negative effects on IQ [AK edit: See also Razib's comment]. But on the whole, this is positive news. Countries with an average IQ of ~95 include Romania, Greece, Turkey, and Israel (!). If the South Asian continent could successfully resolve its malnutrition, parasitic disease load, and inbreeding issues – admittedly, no small challenge – then it could well expect to eventually rise close to southern European living standards.

Vietnam: Phenotypic IQ of 99, versus a genotypic IQ of 106. Certainly a major surprise, considering it is even higher than China. The gap is substantial, but smaller than in India or Africa. This is not surprising, since although Vietnam has the GDP per capita (PPP) of India, it is led by conscientious Communists and is much better off in terms of social development and nutrition (e.g. meat consumption per person is equivalent to that of neighboring, much richer countries). This makes its excellent performance in PISA 2012, which I wrote about in my introductory post on this site, much easier to explain. Consequently, it would also be a strike against Ron Unz’s theory of the East Asian Exception (i.e. that East Asian IQs are very resilient to negative socio-economic and environmental factors). There would still be a substantial gap between Vietnamese genotypic and phenotypic IQ; it’s just that the former are so phenomenally high that the latter can’t help but be very high as well, since Vietnam is at least in terms of social provision no longer a truly Third World country.

China: No gap. Phenotypic IQ (~105) actually higher than genotypic (~104), which is very unusual for a developing country. Here, however, I must stress two things. First of all, with a GDP per capita (PPP) of $12,000, China has already substantially passed the point at which wealth or the absence of it is a significant limiting factor to realizing genotypic IQ potential. Consult this post where I go into this in greater detail in my debate with Ron Unz. Second, I believe that 105 is, at least today, a substantial overstatement of Chinese IQ. My own estimate based on declassified PISA data is 102.5. So that’s already a gap, even if a very small one. But note also that Asian-Americans scored ~107 in PISA 2009, and Asian-Americans in the US include relatively lower IQ Thais, Filipinos, etc. If we set that as the genotypic IQ of the Han people, then there is still very substantial room for further improvement (with the consequence that the Flynn Effect really does apply very much to East Asians too).

Regardless, short of them embarking on some new Maoist adventure, or getting flooded off the world map by runaway global warming, or getting nuked, or some other similarly apocalyptic scenario, China’s and Vietnam’s convergence to at least Japan’s level is all but certain in the long run.


Further to my post on the remarkable failure of Scandinavian education systems to develop their students to anywhere near the levels indicated by their IQ potentials, a professor of mathematics at a Wisconsin university sent me data on the percentage of respondents in the TIMSS who gave the correct answer to the following question:

Which shows a correct method for finding 1/3 – 1/4?

A (1 – 1)/ (4 – 3)
B 1/ (4 – 3)
C (3 – 4)/ (3*4)
D (4 – 3)/ (3*4)

Below are the results. Do bear in mind that these are 8th graders we are talking about.

Korea 2.7 6.9 4.2 86
Singapore 4.8 5.5 6.5 83.1
Taipei 2.9 7.7 7 82
Hong Kong 4 8.7 10 77
Japan 15.4 11.1 8.2 65.3
Russia 12.3 18.8 4.8 62.8
Average 25.4 26 9.4 37.1
US 32.5 26.1 10.7 29.1
Finland 42.3 29.5 8.7 16.1
Sweden 14.4
Chile 11.7

Finally, an international ratings list on which those smarmy, goody-goody Scandinavians don’t come on top! They barely do better than Chile, a country that got 421 (equiv. IQ ~88) in the PISA 2009 survey. Here is what he has to say on the matter:

One interesting fact is that among the 42 countries which tested 8th grade students, Finland had the highest percent of students who picked answer A and the third lowest percent correct. Chile had 11.7 correct and Sweden had 14.4 percent correct. The Finnish result is likely a surprise to the people who have praised the Finnish school system for their results on another international test, PISA. However university and technical college mathematics faculty in Finland will not be surprised. See [this] article signed by over 200 of them.

Anybody who suggests the progressive/neoliberal education policies of the Scandinavian countries are worthy of emulation should be presented with these figures and laughed out of the room.

The results for individual American and Canadian states:

Mass. 21.4 20.8 9.9 44.4
Calif. 28.2 21.6 11 38
Minn. 23.5 26.3 14 35.1
Quebec 27.3 23 13 33
Ontario 27.7 22.4 14 32.5
Conn. 21.8 25.8 17.7 31.3
Alberta 34.7 23.7 12.3 27.8
(Republished from by permission of author or representative)
Anatoly Karlin
About Anatoly Karlin

I am a blogger, thinker, and businessman in the SF Bay Area. I’m originally from Russia, spent many years in Britain, and studied at U.C. Berkeley.

One of my tenets is that ideologies tend to suck. As such, I hesitate about attaching labels to myself. That said, if it’s really necessary, I suppose “liberal-conservative neoreactionary” would be close enough.

Though I consider myself part of the Orthodox Church, my philosophy and spiritual views are more influenced by digital physics, Gnosticism, and Russian cosmism than anything specifically Judeo-Christian.