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.
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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