Introduction
The IQ - short for Intelligence Quotient - is an indicator meant to assess one’s intelligence. Created in the early 1900s, the IQ was, originally, a tool that the German psychologist William Stern designed to identify children in difficulty. Nowadays, the IQ is not quite the same as it used to be. It doesn’t define one’s intellect but his/her capacity to provide an intellectual performance or reasoning. Evaluated by a psychologist, the IQ is now built so that it follows a Gaussian distribution, whose mean is 100 and standard deviation is 15. Therefore, an IQ of 115 or more is considered abnormally high, while a score of 85 or less is considered particularly low, as 68.2% of the population are supposed to have an IQ between these two scores.
As the IQ test became widespread, we have been able to build average IQ statistics that evaluate countries’ average IQ ; and, even though the mean IQ is, by construction, meant to be 100, we can observe huge differences in these IQs. In the past, these gaps have been used to justify a country - or a race, in the sociological sense - superiority over others. Since then, it has been proven that neither race nor ethnicity determine the IQ. More than that, the wide use of the IQ has become controversial as it was created by occidental scientists, so it may be more adapted for occidental individuals. However, that does not mean that we cannot find variables that, at the scale of a country, impact the average score. That is why the question I am addressing here is : what makes the average IQ of a country ?
Literature review
There have been very few researchers or papers trying to assess to causal impact of aggregated variables on the average IQ of countries. Indeed, this area of research is a bit of a minefield as it is often associated to racialism and racism, either because the authors are writing from these perspectives or because their findings are misinterpreted in this way.
The main paper in this field study is probably IQ and the wealth of Nations of Richard Lynn and Tatu Vanhanen (2002). They aimed at establishing a relationship a country’s GDP and its average IQ, and they managed to evidence a positive correlation between them. They also formulated the hypothesis that other variables had to be taken into account, which Lynn and David Becker did with The intelligence of Nations in 2019, as they included temperatures and demographic data, among others, in their analysis. However, these papers’ findings tend to be questioned due to the methodology of the first one : Richard Lynn is a well-known white supremacist accused of adapting his ways of evaluating countries’ average IQ in order to lessen African ones. Not only did it tarnish his reputation, it also made his following studies less credible.
So, as I have not been able to find proper and morally acceptable studies that assess the impact of aggregate variables on the average IQ, I decided to do it myself.
Data
To do so, I relied on data I encountered in here. This website provides data about loads of variables, at scales going from US cities to the world. The main dataset I used displays the average IQ for 199 countries, alongside with a bunch of others variables, such as their total population, area, or even density. However, this dataset only was not sufficient, which is why I added three other ones, also coming from the same website. These datasets include the same variables, except for the fact that the IQ has been replaced by the GDP, the average temperature and the HDI. I merged all these sets into one, which was all the easier as all datasets came from the same source, so used the same country names.
However, I could not directly use them. Indeed, some editing was required since, in each dataset, there were rows that contained one or two more variables than the other (mostly another subregion), and some figures that were not readable correctly by R because of their number of decimal places.
I ended up with a dataset that describes 199 countries, although temperature data is missing for 15 countries and HDI data is missing for 14 countries (all are small countries or countries whose diplomatic situation is tense, such as Taïwan).
With my study, I also wanted to try and assess the impact of being a
former colony on the average IQ. To do so, I identified all the
countries that were colonies at the beginning of the XX° century and
created the dummy variable colony that takes the value 1 if
the country was a colony, and 0 if it was not.
I decided not to consider colonies the countries that were independent before the XX° century because I assumed that the (supposed) effects of colonization on their average IQ would have faded by now (and also, most countries that were counted as colonies gained their independence only 70 years ago, which is not so much).
So, here is what my final dataset looks like.
Descriptive statistics
| Variable | N | Mean | Std. Dev. | Min | Pctl. 25 | Pctl. 75 | Max |
|---|---|---|---|---|---|---|---|
| IQ | 199 | 82.031 | 13.348 | 42.99 | 74.37 | 91.435 | 106.48 |
As shown by this table, the mean average IQ is not 100 - as it should
have been theoretically as the mean IQ is supposed to be 100 - but
82.03, with a standard deviation of 13.35. Two countries can have
drastically different average IQ, as the range of average IQ scores is
no less than 63.49. The median average IQ is 83.13 : it’s Colombia’s IQ
(as its IQ_rank is a 100). So, half of the average IQs are
greater or equal than 83.13, and 75% of them are greater or equal than
74.37 : there is only a few countries whose IQ is “really” low.
All of the graphs and the map (except for the last ones) are interactive : click on countries/bars/bubbles or on the legend to display more information.
| region | Mean_region |
|---|---|
| Africa | 68.25404 |
| Asia | 85.79820 |
| Europe | 94.93786 |
| North America | 78.45276 |
| Oceania | 86.94143 |
| South America | 83.78333 |
As shown by the map, most, if not all, countries with the lowest
average IQ are located in South countries, especially in Africa and
Central America (which are counted as North American countries in my
data). These are also the regions where average IQs are the less regular
and whose mean regional average IQ is the lowest, as shown by
Plot 1 where each dashed line represent the mean average IQ
in the region. Asian average IQs are also relatively irregular, as we
can find among them the highest average IQ (Japan’s) and the lowest
(Nepal’s). However, the mean in Asia is relatively high, as in the three
other regions, whose countries have more similar average IQs.
Plot 2 displays the data from another perspective and
allows to see that richer countries tend to have a higher average IQ
(this positive relationship is represented by the increasing regression
line). Also, each bubble represents a country and its size is
proportional to its population. On the graph bigger bubbles tend to be
on the right, meaning that the more populated the country the richer it
is, but it is hard to make the same statement about the IQ, or at least
the relationship between the average IQ and the population of country
seems weaker than the other one. Finally, the doted line represents the
mean of the average IQs, and once again, it is pretty clear that African
countries are below except for Mauritius, whereas all European ones are
above, except for Albania.
Plot 3 ranks the countries by ascending HDI and shows
their average IQ. Clearly, a strong positive correlation is appearing,
and, most importantly, it seems that the higher the HDI, the more
countries have similar average IQs (they tend to come closer and closer
to the regression line). As we’ll see in the next section, this
relationship was to be expected given the previous one.
