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- Richard Lynn, Helen Cheng and Andrei Grigoriev – 2017 – Differences in the Intelligence of 15 Year Olds in 42 Provinces and Cities of the Russian Federation and Their Economic, Social and Geographical Correlates
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).
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.
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).
Fourth, the PISA scores were significantly correlated at r = .35 (p<.05) with latitude showing that IQs are higher in the more northerly provinces.