That controversial claim that high genetic diversity, or low genetic diversity, is bad for the economy

by Andrew Gelman on January 10, 2013 · 14 comments

in Methodology,Political Economy

Kyle Peyton writes:

I’m passing you this recent news article by Ewen Callaway in the hope that you will make a comment about the methodology on your blog. It’s generated some back and forth between the economics and science communities.

I [Peyton] am very sceptical of the reductive approach taken by the economics profession generally, and the normative implications this kind of research generates. For example, p. 7 of the working paper states: “…[according to our model] decreasing the diversity of the most diverse country in the sample (Ethopia) by 1 percentage point would raise its income per capita by 21 percent”. Understandably, this piece is couched in assumptions that would take hours to pick apart, but their discussion of the approach belies the uncertainty involved. The main response by the authors in defense is that genetic diversity is a ‘proxy variable’. This is a common assertion, but I find it really infuriating. I happen to drink coffee most days, which correlates with my happiness. So coffee consumption is a ‘proxy’ for my happiness. Therefore, I can put it in a regression and predict the relationship between my happiness and the amount of times I go to the bathroom. Ergo universal conclusions: ‘relieving yourself improves mental well being.’ New policy – you should relieve yourself atleast 2 times per day in order to maintain high levels of emotional well being. I know this sound like a South Park episode, but I have heard far worse.

But let’s put the normative implication aside—- what can we learn from star gazing at the tables in this paper?

Here’s the background. 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. Let’s start with the claims on page 7 of their paper:

Once institutional, cultural, and geographical factors are accounted for, [the fitted regression] indicates that: (i) 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 think “CE” is academic jargon for what we call “A.D.” in English (or Latin, whatever), and strictly speaking the above bit is not a claim at all, it’s just an interpretation of their regression coefficients. But it clearly is a claim, in that the authors want us to take these examples seriously.

So let’s take them seriously. What would it mean to increase Bolivia’s diversity by 1 percentage point? I assume that would mean adding some white people to the country. What kind of white person would go to Bolivia? Probably someone rich enough to increase the country’s income per capita. Hey—-it works! What if some poor people from Ethiopia were taken to Bolivia? They’d increase the country’s ethnic diversity too, but I don’t see them increasing its per-capita income by 41 percent. But that’s ok, nobody’s suggesting filling Bolivia with poor Africans.

OK, what about Ethiopia? How do you make it less diverse? I guess you’d have to break it up into a bunch of little countries, each of which is ethnically pure. Is that possible? I don’t actually know. If you can’t do that, you’d need to throw in lots of people with less genetic diversity. Maybe, hmmm, I dunno, a bunch of whites or Asians? What sort of whites or Asians might go to Ethiopia? Not the poorest ones, certainly: why would they want to go to a poor country in the first place? Maybe some middle-income or rich ones (if the country could be safe enough, or if there’s a sense there’s money to be made). And, there you go, per-capita income goes up again.

So I don’t see it. It’s true that later on page 7 the authors try to wriggle out of this one:

Reassuringly, the highly significant and stable hump-shaped effect of genetic diversity on income per capita in the year 2000 CE is not an artifact of postcolonial migrations towards prosperous countries and the concomitant increase in ethnic diversity in these economies. The hump-shaped e§ect of genetic diversity remains highly signiÖcant and the optimal diversity estimate remains virtually intact if the regression sample is restricted to (i) non-OECD economies (i.e., economies that were less attractive to migrants), (ii) non-Neo-European countries (i.e., excluding the U.S., Canada, Australia, and New Zealand), (iii) non-Latin American countries, (iv) non-Sub-Saharan African countries, and, perhaps most importantly, (v) countries whose indigenous population is larger than 97 percent of the entire population (i.e., under conditions that virtually eliminate the role of migration in contributing to diversity).

I don’t buy it. I’m not saying their central point is wrong—-it’s basically a twist on the classic “why are some countries so poor” question—-but the extrapolations that they give themselves reveal the problems with their interpretation of the regression model. The way you make Bolivia more diverse is by adding more white people. It’s fine to study these things but you have to think about what your models mean.

Everybody wants to be Jared Diamond, that’s the problem.

OK, if all this is the case, what went wrong, and how could Ashraf and Galor have done better? I think the way to go is to start with the big pattern they noticed: the most genetically diverse countries (according to their measure) are in east Africa, and they’re poor. The least genetically diverse countries are remote undeveloped places like Bolivia and are pretty poor. Industrialized countries are not so remote (thus they have some diversity) but they’re not filled with east Africans (thus they’re not extremely genetically diverse). From there, you can look at various subsets of the data and perform various side analysis, as the authors indeed do for much of their paper.

The problem is closely related to their paper appearing in a top journal. The way I see this work, the authors have an interesting idea and want to explore it. But exploration won’t get you published in the American Economic Review. Instead of the explore-and-study paradigm, Ashraf and Galor are going with assert-and-defend. They make a very strong claim and keep banging on it, defending their claim with a bunch of analyses to demonstrate its robustness. I have no problem with robustness studies (recall that I was upset about some claims about age and happiness because I had difficulty replicating them with new data), but I don’t think this lets you off the hook of having to think carefully about causal claims. And presenting tables of numbers to three (meaningless) decimal places doesn’t help either.

High-profile social science research aims for proof, not for understanding—-and that’s a problem. The incentives favor bold thinking and innovative analysis, and that part is great. But the incentives also favor silly causal claims. In many social sciences, it’s not enough to notice an interesting pattern and explore it (as we did in our Red State Blue State book). Instead, you’re supposed to make a strong causal claim even in a context where it makes little sense.

{ 14 comments }

Marc Ross January 10, 2013 at 6:04 pm

It would be good if economists producing this kind of finding would sometimes bother to at least identify the plausible underlying mechanisms at work. How is genetic diversity perhaps related, and causally connected, to economic development?

ricketson January 10, 2013 at 6:24 pm

Here’s my speculative mechanism:

Genetic diversity has two benefits for development:
1) Hybrid vigor creates stronger individuals, longer lives, and greater productivity.
2) Physiological diversity allows for more effective economic specialization (only useful in advanced economies)

I don’t have such easy explanations for how genetic diversity decreases development. One possibility is that people are naturally “racist” and view people with very different phenotypes (e.g. skin color, height) as being foreigners and are less willing to cooperate… so diverse societies have less cooperation.

The problem is that these are still post-hoc explanations and quite speculative in their own right.

Don Fine January 11, 2013 at 2:40 am

It would be good if some of us would read the argument rather than speculate about it. The authors do identify the mechanism trough which genetic diversity operates and confirm it empirically.

They write:
“Second, there exists an optimal level of diversity for economic development, reflecting the interplay between the opposing effects of diversity on the development process. The adverse effect pertains to the detrimental impact of diversity on the efficiency of the aggregate production process. Heterogeneity raises the likelihood of disarray and mistrust, reducing cooperation and disrupting the socioeconomic order. Higher diversity is therefore associated with lower productivity, which inhibits the capacity of the economy to operate efficiently relative to its production possibility frontier. The beneficial effect of diversity, on the other hand, concerns the positive role of heterogeneity in the expansion of society’s production possibility frontier. A wider spectrum of traits is more likely to contain those that are complementary to the advancement and successful implementation of superior technological paradigms. Higher diversity therefore enhances society’s capability to integrate advanced and more efficient production methods, expanding the economy’s production possibility frontier and conferring the benefits of improved productivity.”

ricketson January 10, 2013 at 6:12 pm

As I understand it, CE means “common era”. It’s ineffective political correctness … they try to include non-Christians by dropping the expression “the year of our lord”, but then pretend that the estimated year of the birth of Jesus of Nasareth somehow marks the origin of global civilization. I think we should start using Magellan’s circumnavigation to mark year 0.

Bernard Winograd January 10, 2013 at 7:24 pm

Do they mean the genetic diversity of the population or of the individuals in the population? There is a big difference and the genetic diversity of African populations is HIGHER than other populations. And do they really mean genetic diversity or are they talking about ethnicity? The effort to find a genetic basis for human perceptions of race and ethnicity has been pretty hard going….

kyle January 10, 2013 at 9:19 pm

According to the WP, they are measuring genetic diversity within populations as opposed to ‘between’ populations. I understand the between societies approach to be that used to measure the role social and cultural differences might play in explaining the variation in economic differences between countries. The thing that immediately comes to mind to me is Protestant Work Ethic or similarly, claims that social and cultural differences between countries explain variation in attitudes about corruption. They cite the within approach as one of their many contributions. From the paper:

“[Spolaore andWacziarg (2009)] show that Fst genetic distance, a measure that re‡flects the time elapsed since two populations shared a common ancestor, confers a statistically signifi…cant positive effect on both historical and contemporary pairwise income differences. In contrast, the genetic diversity metric within populations exploited by this paper facilitates the analysis of the effect of the variation in traits across individuals within a society on its development process.”

Don Fine January 11, 2013 at 2:51 am

Since most countries consist of many ethnic group the index that Ashraf and Galor construct account for both. They write: “The second, more complex strategy
involves the construction of an index of genetic diversity for contemporary national
populations that accounts for the expected heterozygosity within each subnational
group as well as the additional component of diversity at the country level that
arises from the genetic distances between its precolonial ancestral populations. The
examination of comparative development under this second strategy would have to
account additionally for the potential inducement for members of distinct ethnic
groups to relocate to relatively more lucrative geographical locations. “

kyle January 10, 2013 at 9:20 pm

I sent this article some time ago and after re-reading the original piece (forthcoming in the AER) I still don’t understand what definition of ‘causality’ they’re using. Andrew makes a good point about proof v. understanding. I had the occasion to re-read Akerlof’s famous paper: “The Market for “Lemons”: Quality Uncertainty and the Market Mechanism”. A classic econ paper that I think exemplifies the type of explore and study research that can be both highly useful and high profile (it has more than 8k citations on google scholar). I was not surprised to learn that it was rejected by several of the top econ journals including the AER which apparently did so because of its ‘triviality’ (see: http://www.nobelprize.org/nobel_prizes/economics/laureates/2001/akerlof-article.html)

Thomas January 10, 2013 at 9:23 pm

From a quick skim of the article it seems that you can tell an identical story by substituting in “proximity to ancient trade routes” for “genetic diversity”. We know from previous genetic studies that genetic diversity increases along trade routes. So conceivably it was good to be somewhat close to a trade route and have access to goods, but being too close to a trade route also led to conflict (e.g. Sicily was conquered by multiple tribes) that retarded growth. I think this makes more sense than their purely sociobiological model as a mechanism of growth.

Don Fine January 11, 2013 at 2:58 am

Again a superficial reading of the paper could have addressed this question. Ashraf and Galor wrote an entire section refuting this alternative hypothesis. See “Robustness to Aerial Distance and Migratory Distances from Placebo Points of Origin across the Globe”

Neville Morley January 11, 2013 at 6:17 am

To be fair to the authors of the paper, they do a good job in skirting round some of the usual problems with crude sociobiological models: most obviously, they seek to steer well clear of what readers of a certain persuasion would be inclined to draw from a superficial reading of their abstract, namely that some ethnic groups are simply more productive and more open to innovation and entrepreneurship than others.

But that leads them straight into what is, for me, the major problem with the paper: how to bring together the empirical data on genetic diversity within specific ethnic groups (which can, plausibly if not incontrovertibly, be connected to the ‘Out of Africa’ migration hypothesis they favour) and the empirical data on economic performance, in a manner that still manages to exclude the last few centuries of history (they mention themes like colonialism and globalisation solely in order to discount them). The problem is that the economic data doesn’t come packaged by ethnic groups (and if it did, that would lead them towards the sorts of conclusions that they’re eager to avoid), but rather by nations or regions that generally contain a mixture of ethnic groups – and both the nature of that mixture, and the definition of the nation itself, are manifestly modern phenomena, closely related to precisely the sorts of historical processes that they wish to discount in favour of an underlying genetic explanation.

It’s precisely their attempt to connect the two sets of data that I find unpersuasive, but that’s the heart of the paper. An interesting hypothesis, and I entirely agree with the sentiment that this would be better as an exploration of the issues than a dogmatic assertion of conclusive findings. I wonder whether this isn’t just a reflection of the incentive system in social science publishing, but also another example of the long-standing tendency for economists (more than most social disciplines, in my experience) to seek to assert dominance over other fields: they don’t need to worry about anything anthropology has to say, they understand history better than the historians (cf. their glib assertions on the Roman Empire) and so forth.

Neville Morley January 11, 2013 at 6:19 am

Oops: “…the economic data don’t… and if they did…”

Marc Ross January 11, 2013 at 11:08 am

Kyle points to two policy implications from this piece–sending more white people to diversify Bolivia and splitting Ethiopia into smaller more homogeneous states. The simpler solution however might be to simply move some small Ethiopian groups to Bolivia. But if he is committed to sending white folks to Bolivia there are many gun owning Texans who might be just right.

Scott January 14, 2013 at 7:41 pm

RE: CE. CE refers to the “Common Era” and BCE is “Before the Common Era,” which is another way of marking the Christian calendar. My rabbi where I grew up was quite conservative and argued adamantly that using BC (“before Christ”) and AD (“Anno Domini”) was unacceptable for Jews and that they shouldn’t use it in their everyday writing. These terms are inherently discriminatory, because they have an inherently Christian bias. He favored instead what Ricketson calls “awkward political correctness.” Probably, but it only works if everyone else understands what these terms are referring to. I’m not sure about scientific publications that work with data from “before Christ,” whether natural or social sciences, but I don’t think the use of CE and BCE are common enough yet for authors to be even be given credit for using these abbreviations. But small kudos to them for trying, maybe.

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