In the last post we saw that the evidence is not kind to the idea that the causal direction goes from GDP to IQ in the observed relationship. However, this does not yet establish, that the causality goes into the opposite direction. In theory, there are two other possibilities to take into account.
One, there might be a third variable that is causally influenced by both GDP and IQ. If we somehow unwittingly controlled for this variable, while collecting the GDP and IQ data, we would have introduced a spurious correlation. This seems to be extremely unlikely for our data.
Two, it is possible that there is an a third variable that influences IQ and that is not causally influenced by GDP, such as “industrialisation”. If industrialisation increases IQ, but just being wealthy does not, it would be small wonder that we see no IQ increase in countries that have gotten rich by different means.
However, if we can explain a big portion of the IQ differences with a different variable, whose value has been fixed before environmental influences like industrialisation could have worked their magic, this kind of confounding becomes very unlikely.
So, here we go one step deeper and take a look at the ethnic makeup of different countries.Todays percentages of different ethnic groups in the countries we are going to investigate are overwhelmingly due to immigration that happened many generations ago, sometimes hundreds of years. If we can explain some of the IQ and GDP differences via ethnic composition, it seems quite unlikely that they are caused by environmental influences.
In South and Middle America the percentage of people who identify as “white” correlates 0.66 (p<0.0054) with GDP and 0.838 (p<5.06e-05) with IQ. (Given that the newest database contains gems like an IQ below 50 for Nicaragua, we use Rindermann’s IQ database, which is based on educational assessment studies. Those have fewer of the problems with sampling and Flynn effect correction that the pure IQ studies are prone to. We also exclude all Islands. Mostly because avoiding modelling black percentage as well is simpler. The information of white self-identification was mostly collected from the respective wiki-articles and is based on census information.)
If we just look at the Islands, IQ and black percentage correlates -0.585 (p<0.028).
In South-East Asia the percentage of Chinese per country  correlates 0.9948 (p<3.154e-08) with GDP per capita and 0.858 (p<0.003016) with mean IQ. Of course, here the high values are driven by the outlier Singapore, but at least the insane GDP-Chinese correlation hardly diminishes if we exclude Singapore.
In Africa, there are several countries, that have a small white minority . These are descendants of white settlers from up to 400 years ago. If you plot the percentage of white Africans against GDP, there is no correlation. However, the outliers are systematic. If we exclude Botswana, which is wealthy due to diamonds and other minerals, as well as Gabon and Equatorial Guinea, two neighboring states rich in oil, the picture changes significantly.
Among Sub-Saharan countries, which do not depend strongly on natural resources, the white percentage correlates 0.86 (p<0.00065) with GDP. This is really astonishing, because the overall percentages are so small. Also, the remaining outlier Mozambique can likely be explained by a long civil war (1977-1992) and lingering political instability.
This data implies that ethnic composition has a lot of explanatory power when it comes to GDP differences. Because the ethnic composition was mostly determined hundreds of years ago, it seems likely that it causally drives GDP differences. Our previous investigations and the correlation between IQ and ethnic composition suggest, that the causal connection between ethnic composition and GDP is at least partially mediated by IQ.
 Chinese diaspora
 White Africans