African IQ and the Flynn effect
The average African
African cognitive ability based on international assessments
When it comes to calculating the average African cognitive ability based on international assessment tests, there is disagreement about which method to use when transforming the test scores into IQ equivalents. Rindermann uses direct transformation, Lynn prefers equalization of means and standard deviations, and Wicherts prefers regression .
Using the data that Lynn and Meisenberg (2010) give, I computed the African average cognitive ability based on direct transformation, equalization of the means, and regression (data here).
The following countries have at least 1 data point : Mozambique, Nigeria, Swaziland, South Africa, Botswana, Ghana, Zimbabwe The following assessments were included: TIMSS 95‘, TIMSS 97‘, TIMSS 03‘, PIRLS 06’ Reading, IAEP Math 90‘, IAEP Reading 91‘, SISS 83‘, SIMS 81’)
Lynn argues that these scores are inflated as a result of low student attendance rates (e.g. low IQ adolescents didn’t attend as frequently in the past) and as a result of the inclusion of tests which were not based on item response theory. If this is true, we should find lower scores on the more recent tests, as they are based on IRT and as the African school attendance rates have increased. After removing the Second International Science Study (83’) and the Second International Math Study (81‘), the only tests included from the 80’s, the average scores decrease ~3 points. The decrease confirms Lynn’s view.
There’s no easy resolution to the issue of which method to use and to the issue of which scores to count. At best, we can estimate that the African cognitive ability based on all assessments is 76 ± 5, and we can note that the average is trending downward, a trend which coincides with increased rates of enrollment and increased accuracy of measurement. Given that the African cognitive ability based on more recent assessments is 73± 6, I would offer 73 as the cognitive ability (as assessed by international tests) and note that this figure takes into account attendance rates and other factors.
African cognitive ability based on IQ tests
When it comes to calculating the average African cognitive ability based on IQ tests, there is disagreement about which inclusion criteria to use and there is disagreement about the meaning of the scores [1-4].
Below, I listed Wicherts’ estimate and Lynn’s estimate (as recalculated by me) in addition to the N-weighted average of every test mentioned in 1-5]
The following countries have at least 1 data point: Congo, Ethiopia, Ghana, Mali, Nigeria, South Africa, Zaire, Kenya, Malawi, Nambia, Sudan, Uganda, Zimbabwe, Madagascar
(Non-Raven’s IQ data here.)
Based on their systematic review of the data and rigorous inclusion criteria, Wicherts et al calculate an average African IQ of 76.5 . Based on the studies deemed representative by Lynn, I calculated an average African IQ of 71 [1,2]*; the summed data mentioned by Lynn and Wicherts, rejected and not, averaged out to an IQ of 73**. I would offer 73 as the true African cognitive ability based on IQ; while this figure is derived from data which includes numerous unrepresentative samples (e.g. IQ tests given to children with parasite infections; IQ tests given to elite university students), the upward and downward biases tend to cancel out. The close agreement between IQs derived from Raven’s matrices, IQs derived from other IQ tests, and IQ equivalents derived from international assessments, factoring in attendance and age, supports this conclusion.
*Lynn corrects student scores down for representativeness. I uncorrected for that. I also excluded Adult CPM scores (above 18) based on Wicherts’ concern; (Wicherts excludes above 11).
**There is disagreement about a few of the scores; I averaged the difference of the disputed amount.
Taking the international assessments and IQ tests together, the measured African cognitive ability stands at
The meaning of African IQs
IQ is a measure of general intelligence. It can be a poor measure or a good measure. Wicherts et al,  found the following for Raven’s matrices:
The above indicates that Raven’s matrices are poorer measures of g for Africans than for Westerners. The implications of this for the African IQ are not clear.
The African IQ and the Flynn effect
Wicherts et al (2010) contend that the African IQ will markedly increase in the near-term due to the processes underlying the Flynn effect . They show that there has been a steep score increase in the samples of African IQs that they deem representative.
Is the African IQ really skyrocketing? Is the Congo student IQ really now around 120-something? Using the complete IQ data bank, I plotted the increase in African IQs over time. There is disagreement about several of the sample scores. The graph on the left is based on a minimalistic exclusion criteria with judgement calls made by me. The graph on the right is based on a minimalistic exclusion criteria with judgement calls made by Wicherts et al. The rationale for using the complete data bank is that the complete bank presents a better picture of “the African IQ”; sampling bias at either ends (e.g university students and tribal children) will cancel each other out. The overlap of the African Average calculated using the complete bank and the average derived from international assessments supports this contention. (Note: I used the un-weighted means, so the average IQs are slightly inflated in these graphs. The weighted means were 73.1 and 74.3 for the first and second graph, respectively.)
The regression lines show that the African IQs have been fairly constant across time relative to UK norms. If an accelerated Flynn effect was occurring in Africa, such that the African and Western averages were due to intercept in the near-term, we would expect a positive slope of more the negligible magnitude. If the Flynn effect had yet to hit Africa, we would expect a negative slope, as the Western scores should have risen over time relative to the African scores. The Flynn effect seems to have occurred in African in tandem with the West. The African Flynn effect found by Wicherts et al. appears to have been a result of sampling bias.
For further confirmation of this, I plotted the international test score equivalents (calculated using equalization of the means) over time (K = 17). Were Wicherts et al. correct, see the figure at the top of the page, the African student scores should show an increase corresponding to their supposed IQ increase. They don’t. Rather, the African student scores show a decrease in tandem with increased enrollment and increased test sophistication.
 Lynn and Meisenberg, 2010. The average IQ of sub-Saharan Africans: Comments on Wicherts, Dolan, and van der Maas
 Lynn, 2010. The average IQ of sub-Saharan Africans assessed by the Progressive Matrices: A reply to Wicherts, Dolan, Carlson & van der Maas; Lynn and Meisenberg
 Wicherts, et al., 2010. The dangers of unsystematic selection methods and the representativeness of 46 samples of African test-takers
 Wicherts, et al., 2010. Raven’s test performance of sub-Saharan Africans: Average performance, psychometric properties, and the Flynn Effect
 Wicherts, et al., 2010. A systematic literature review of the average IQ of sub-Saharan Africans
 Brouwers, et al., 2009. Variation in Raven’s Progressive Matrices scores across time and placeSymen A. Brouwers
 Rindermann, et al., 2009. The impact of smart fractions, cognitive ability of politicians and average competence of peoples on social development Between nations.