Back in 2013, I wrote a post regarding a controversial claim that high genetic diversity, or low genetic diversity, is bad for the economy:
Two economics professors, Quamrul Ashraf and Oded Galor, wrote a paper, “The Out of Africa Hypothesis, Human Genetic Diversity, and Comparative Economic Development,” that is scheduled to appear in the American Economic Review. As Peyton has indicated, the paper is pretty silly and I’m surprised it was accepted in such a top journal. Economists can be credulous but I’d expect better from them when considering economic development, which is one of their central topics. Ashraf and Galor have, however, been somewhat lucky in their enemies, in that they’ve been attacked by a bunch of anthropologists who have criticized them on political as well as scientific grounds. This gives the pair of economists the scientific and even moral high ground, in that they can feel that, unlike their antagonists, they are the true scholars, the ones pursuing truth wherever it leads them, letting the chips fall where they may.
The real issue for me is that the chips aren’t quite falling the way Ashraf and Galor think they are. . . . Everybody wants to be Jared Diamond, that’s the problem. . . .
And in 2016 I followed up with a post, “Why is Africa so poor while Europe and North America are so wealthy?”:
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 . . .
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 . . . 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. . . .
In the meantime (actually, before my 2016 post), various experts have written more on the topic.
There’s this 2015 paper, “Heterogeneity and Productivity,” by Ashraf, Galor, and Klemp, which begins:
This research explores the effects of within-group heterogeneity on group-level productivity within a novel geo-referenced dataset of observed genetic diversity across the globe. It establishes that observed genetic diversity of 230 worldwide ethnic groups, as well as predicted genetic diversity of 1,331 ethnic groups, has a hump-shaped effect on economic prosperity, reflecting the trade-off between the beneficial and the detrimental effects of diversity on productivity. Moreover, the study demonstrates that variations in within-ethnic-group genetic diversity across ethnic groups contribute to ethnic and thus regional variation in economic development within a country.
Also in 2015, Noah Rosenberg and Jonathan Kang published a paper, “Genetic Diversity and Societally Important Disparities,” which begins:
The magnitude of genetic diversity within human populations varies in a way that reflects the sequence of migrations by which people spread throughout the world. Beyond its use in human evolutionary genetics, worldwide variation in genetic diversity sometimes can interact with social processes to produce differences among populations in their relationship to modern societal problems. We review the consequences of genetic diversity differences in the settings of familial identification in forensic genetic testing, match probabilities in bone marrow transplantation, and representation in genome-wide association studies of disease. In each of these three cases, the contribution of genetic diversity to social differences follows from population-genetic principles. For a fourth setting that is not similarly grounded, we reanalyze with expanded genetic data a report that genetic diversity differences influence global patterns of human economic development, finding no support for the claim. The four examples describe a limit to the importance of genetic diversity for explaining societal differences while illustrating a distinction that certain biologically based scenarios do require consideration of genetic diversity for solving problems to which populations have been differentially predisposed by the unique history of human migrations.
So, the economists go with a biological explanation for economic disparities, but the biologists disagree. Rosenberg summarizes in an email:
Something that might be considered different in this critique of Ashraf & Galor (2013) is that the critique is accompanied by detailed descriptions of several topics where genetic diversity has a clear impact on socially consequential variables that differ across populations (e.g. transplantation match probabilities), and by a discussion of the distinction that separates Ashraf & Galor (2013) from those other topics. We would hope that the line of work that computes correlations between economic variables and features of population-genetic data will recognize the distinction between fundamentally nonbiological uses of the population-genetic variables and scenarios where the utility of those variables is based in biology.
I don’t have anything new to add beyond my 2013 post, really. Anyone who’s interested can go to these papers and read more.
As much as I enjoy/am-enlightened-by seeing studies set up like so many tin cans on a fence rail and used for methodological target practice the experience would be even better if you would also address (a) whether the theory is even practicably testable and (b) if it is, what sort of test (and result) you would find actually compelling.
But I really came here to ask if this is as funny as I think it is: https://pbs.twimg.com/media/DneI1nkXsAAsp2l?format=jpg&name=medium
Once again proving that there’s an XKCD for every occasion https://xkcd.com/2048/
I may use that as the cover slide for my next presentation, doesn’t really matter what the presentation is about.
But do you have enough points to make the elephant wag its trunk?
That is fantastic. I want T-shirts made.
https://twitter.com/Corey_Yanofsky/status/1042459894983667712
As an economist, I never could buy into the Ashraf and Galor thesis. The reason why economists are interested in economic growth is mainly due to what has happened in the last 300 years to living standards. It is only a mere possibility that genetic diversity has much to do with that growth. Historical measures of GDP per capita are not great, but genetic diversity seems unlikely to explain why the America colonies had higher per capita income than England, why South Korea has a higher income than North Korea, why Singapore and Taiwan have higher incomes per capita than Malaysia and China, or why England of 1700 was much poorer than the England of 1900.
Going back farther, one can’t help but think that genetic diversity doesn’t provide any insight into why Athens of 900 BC was much poorer than the Athens of 400 BC.
Are we to attribute the United States economic growth in the 19th and 20th centuries to genetic diversity that comes through immigration rather than through the more obvious mechanism of specialization being limited by the extent of the market identified by Adam Smith in the first chapter of the Wealth of Nations?
Maybe genetic diversity has an effect on economic growth, but my guess is that it is way down on the list of factors that contribute to economic growth, right above penis size and right below the yearly average distance to Jupiter (better log that variable).
Genetic diversity does not have to be a useful explanatory variable always to be a useful explanatory variable sometimes.
Primitive economy might be be insensitive to slight variations in specific cognitive abilities while a more more sophisticated economy will be much more IQ-sensitive. Native population’s low ability can be overwhelmed by the high ability of the newcomers, and so you will see growth wit the increase of diversity (as well as the relatively high average ability of the natives can be swamped by the low ability migrants, and so increase of diversity will be correlated with economic decline). Or these things can lead to a complicated dynamics. If most of the post industrial revolution economic grows is driven by highly skilled labour and cognitive abilities, and these skills/abilities are distributed unevenly one would expect that in the last 200 years importance of certain variations will increase dramatically.
But sure, it’s a correlational study.
I have no doubt IQ has something to do with economic growth (see Garret Jones’ Hive Mind for an example). And you are right that some traits will be more beneficial for economic growth while others not so much. But that is not the hypothesis of Galor and Ashraf. Their papers are on genetic diversity as a whole, and it is not about phenotype diversity but genotype diversity. The physical manifestations of genes (which they don’t study), not the genes themselves, are what will have an impact on growth. I don’t know how correlated the two are, but I imagine that the correlation varies dramatically depending on which trait is being studied. And given that many important traits are produced not by single genes but by complex interactions between genes, it really isn’t clear what the link between genetic diversity and phenotypic diversity would be.
I take your point that it might be a useful explanatory variable some of the time, but one issue here is that Ashraf and Galor don’t do an analysis to find out when it is a useful explanatory variable and when it is not. They use it as *the* explanatory variable.
Replace “genetic diversity” with “genetics” in the above and things get much more interesting.
Replace genetic with racial and it’s 1918 all over again, complete with casual dismissal of any criticism that such analyses are misguided and objectionable. Rather it’s a reassertion that’s it’s hardboiledvscience of letting the facts fall where they may and thus beyond reproach. Rather it is a matter that only serious men will rise to the challenge to conduct well-reasoned, methodologically sound, and statistically rigorous analyses. Rather it is about benign but intellectually interesting puzzles for which clever repartee can be displayed. You can measure power by the degree of low self-awareness. It’s Groundhog Day
Gatherdust:
See here for further discussion of this point.
Trying to link economies to genes = premium grade genobollox.
An avalanche of which is on its way, courtesy of Plomin’s new book
eg “have to completely rethink and rebuild the social sciences”
https://quillette.com/2018/09/25/forget-nature-versus-nurture-nature-has-won/
Perhaps the idea of “causal distance” caution can help.
Unless factors are proximate, or no more than 1 or 2 steps removed from proximate, extra caution about correlations is warranted.
And this also falls into the variation trap, see
“Causes of changes in X… need not be causes of X”
https://bigthink.com/errors-we-live-by/judea-pearls-the-book-of-why-brings-news-of-a-new-science-of-causes
+1 I don’t think that causal distance is sufficient to capture the level of nonsense here. I think that we are talking about two completely different systems: one biological and one social. They have different ontologies, that is, if you formalized the theories in Tarskian model theory, you would see that the variables range over different objects. In the case of the biological system, we would have things like genes and proteins and whatever. In the case of the social/economic system, we will need people, beliefs, preferences, etc. Without an actual reduction of the one system to the other, it is just a theological belief to assert that the one system is influencing the other. It is as if someone wanted to explain the outcome of a chess game by invoking quantum mechanics. The fact that the chess pieces are physical objects does not mean that physics could provide a useful explanation of a chess game. Checkmate is not a physical state. Likewise, wealth or income or GDP are not biological states. Reductionism is a great scientific hypothesis that has lead to great discoveries and actual reductions of one system to another. It should not be treated as dogma, but as an extraordinary claim that requires proof whenever asserted.
> The fact that the chess pieces are physical objects does not mean that physics could provide a useful explanation of a chess game. Checkmate is not a physical state.
I think it’s important to realize that absolutely everything that happens *is* a physical state, including thinking the words “Checkmate is not a physical state”
It’s not that physics is a *useful* level of abstraction for describing chess, but at least the level of abstraction you use shouldn’t violate fundamental ideas in physics. Like you can’t play chess with someone far away unless you wait long enough for light signals to reach them and return. SO if you want to play timed chess, you have to include the transmission time in the game, and if you want to play with 6ft high granite pieces you’d better bring a crane.