A few years ago, two economics professors, Quamrul Ashraf and Oded Galor, published a paper, “The Out of Africa Hypothesis, Human Genetic Diversity, and Comparative Economic Development,” that drew inferences about poverty and genetics based on a statistical pattern. The world’s most genetically diverse countries (using their measure of what counts as genetically diverse) are in sub-Saharan Africa, which is the world’s poorest region. The least genetically diverse countries are in places like Bolivia, which have low incomes but not as low as in that region of Africa. There’s an intermediate level of genetic diversity among the residents of the middle-income and rich countries in Asia, Europe and North America.
Genetic diversity arises from migratory distance of populations from East Africa. Countries in east Africa have the highest genetic diversity because this is where humans evolved. Populations that settled in other parts of the world descend from various subgroups of people who left Africa at different times. Thus, these groups are less varied in their genetic profiles.
Ashraf and Galor put this together and argued that this is “reflecting the trade-off between the beneficial and the detrimental effects of diversity on productivity.” Their argument was that a little bit of genetic diversity is a good thing because “a wider spectrum of traits is more likely to be complementary to the development and successful implementation of advanced technological paradigms,” but if a country is too genetically diverse, its economy will suffer from “reduced cooperation and efficiency.” Thus, they wrote, “the high degree of diversity among African populations and the low degree of diversity among Native American populations have been a detrimental force in the development of those regions.”
Any claim that economic outcomes can be explained by genes will be immediately controversial. It can be interpreted as a justification of the status quo, as if it is arguing that existing economic inequality among countries has a natural, genetic cause. See this paper by Guedes et al. for further discussion of this point.
When the paper by Ashraf and Galor came out, I criticzed it from a statistical perspective, questioning what I considered its overreach in making counterfactual causal claims such as:
… increasing the diversity of the most homogenous country in the sample (Bolivia) by 1 percentage point would raise its income per capita in the year 2000 CE by 41 percent, (ii) decreasing the diversity of the most diverse country in the sample (Ethiopia) by 1 percentage point would raise its income per capita by 21 percent.
I argued (and continue to believe) that the problems in that paper reflect a more general issue in social science: There is an incentive to make strong and dramatic claims to get published in a top journal.
Monkey Cage newsletter
Commentary on political science and political issues.
My criticisms were of a general sort. Recently, Shiping Tang sent me a paper criticizing Ashraf and Galor from a data-analysis perspective, arguing that their effect goes away after including allowing for a “Eurasia” effect, from Jared Diamond’s hypothesis in his book, “Guns, Germs, and Steel” that Eurasia had an economic advantage from two sources: the availability of domesticable animals and a more favorable geography in that innovations could be spread along east-west rather than north-south axes, with these two features favoring the development of agricultural societies.
Tang writes:
… we provide a systematic econometric rebuttal against Ashraf and Galor, based on Ashraf and Galor’s (2012) own data. We do not question the possible link between migratory distance and predicted genetic diversity: We give Ashraf and Galor the benefit of doubt that migratory distance is a good proxy for predicted genetic diversity. Neither do we challenge the link between genetic diversity and innovation or the link between genetic diversity and cooperation/conflict, although we do wish to note that the case presented by Ashraf and Galor (2012) on these two possible causal links has been weak at best. . . . Finally, we do not even challenge the data collected by Ashraf and Galor: We assume that all of their data are valid and accurate. Instead, we attempt to unambiguously show that even with their own data, Ashraf and Galor’s (2012) results cannot hold after controlling for a key variable that is missing in their inquiry.
I have not tried to evaluate the details of Tang’s reanalysis because I continue to think that Ashraf and Galor’s paper is essentially an analysis of three data points (sub-Saharan Africa, remote Andean countries and Eurasia). It offered little more than the already-known stylized fact that sub-Saharan African countries are very poor, Amerindian countries are somewhat poor, and countries with Eurasians and their descendants tend to have middle or high incomes.
That said, this new paper by Tang could be useful in that it criticizes Ashraf and Galor on their own terms.
