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 such as 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 the migratory
distance of populations from East Africa. Countries in East Africa have
the highest genetic diversity because that 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
criticized 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.
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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 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 re-analysis 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.
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