Thinking

The Tyranny of the Isotherms: Evidence from High Resolution Data

One of my great frustrations has been that I have yet to learn cartographic software. But having chanced upon Yale’s G-Econ high resolution data, I have suddenly found myself in a position to create virtual maps. So that’s the occasion for revisiting an old obsession. Basically, I have been trying to get a handle on global polarization. Why is wealth and power so goddamn concentrated on our planet?

The short answer is the tyranny of the isotherms. I have identified at least three causal channels from the Heliocentric geometry of our lifeworld to global polarization. First, thermal burdens directly suppress productivity since work intensity cannot be sustained on the same machine at northern rates in southern climes due to the human thermal balance equation. You must take frequent breaks to prevent overheating. This means that low latitude nations find it hard to compete for global production against high latitude countries. Biogeography thus directly conditions the global division of labor.

Second, higher thermal burdens closer to the equator come with higher disease burdens. This is simply because germs, parasites, and disease vectors proliferate in the tropical and subtropical zones. (More generally, species diversity and overall biomass is much greater in the tropics.) The attendant health insults indirectly suppress productivity by sapping the strength of populations situated closer to the equator. As Gamble put it in context of the Out-of-Africa dispersals, the low latitudes were good areas to escape from.

dengue

Third, since development is strongly path dependent, ecogeographic factors such as Binford’s storage threshold (food cannot be stored when ET is above 15.25ºC; ie within the two darkest bands in the contour map below), the length of the growing season (also captured by ET), and net above-ground productivity (not sufficient for survival on vegetal sources when ET is below 12.75 ºC; ie within the two lightest belts in the map below) constraint the long-term trajectories of societies in a manner that is decidedly not neutral. In general, the incentives and possibilities for technical innovation and capital accumulation senso lato are higher at high latitudes where the length of the growing season is limited (one must save for the winter or one will literally starve) and net above-ground productivity is low (every calorie requires more work to secure thereby incentivizing technical innovation). At low latitudes on the other hand, above-ground productivity is high, the growing season lasts through the year (there are effectively no seasons when ET is above 18ºC; the darkest zone in the map below), and food storage is impossible anyway, so there is little incentive to save for lean times or invest in labor saving innovations. Binford showed that across the ethnographic present, the tool-kits of hunter-gatherer increase in complexity as ET falls.

highreset

Binford’s thresholds for ET. Darkest band: ET>18ºC, zero days of frost; second band: 18>ET>15.25 storage threshold; third band: 15.25>ET>14 Bailey’s threshold for cool and warm climes; fourth band: 14>ET>12.75, exclusive reliance on vegetal resources impossible; penultimate band: 12.75>ET>10, frost all year; lightest band: ET<10ºC, polar climate.

HighResPCGDP.png

So what does empirical evidence have to say? The G-econ dataset has income, population and environmental data at the resolution of latitude and longitude grids. The above map displays per capita income at purchasing power parity in 2005. We have N=18,683 observations in the sample. We begin by estimating Spearman’s rank correlation coefficient between ET and per capita income. Our is estimate is extremely high (r=-0.6103, p=0) and so significant that the p-value is indistinguishable from zero within machine precision. That ET alone explains 37 percent of the variation in per capita income at this fine-scale resolution is nothing short of mind-boggling.

We had previously tried in vain to test the Heliocentric theory with within country data. Specifically, it is a prediction of the theory that nations that span isotherms should be regionally polarized by ET. We can now test that prediction. Our estimate for Italy (r=-0.7642, p=0) is even higher than the global sample and again so significant that p=0 with machine precision. For Chile, our estimate is also very significant (r=-0.3946, p<0.0001) but not as strong as that for the United States (r=-0.5218, p<0.0001) or Argentina (r=-0.6098, p<0.0001). More generally, we find that a statistically significant (p<0.05) relationship holds in 41 countries. We do however fail to find a significant correlation in China (r=0.06, p=0.9762).

To check for robustness we return to the global dataset and control for various factors. Recall our baseline estimate for the correlation between ET and per capita income (r=-0.6103, p=0). We begin by controlling for altitude. Our estimate for the partial correlation coefficient is marginally higher (r=-0.6360, p=0). Controlling for both annual precipitation and altitude, our estimate is marginally lower (r=-0.6009, p=0). Controlling also for distance from the ocean (which measures continentality—the climate is more temperate closer to the ocean than further inland) we obtain a very similar figure (r=-0.6291, p=0). Similarly, controlling for altitude, precipitation, distance from the ocean, and distance from a major river leaves our estimate essentially unchanged (r=-0.6298, p=0). Controlling further for area of the grid (the “squares” reduce in size away from the equator) marginally reduces our estimate (r=-0.5750, p=0). This is likely because the area of the grid is a function of latitude. We therefore drop area and control for roughness (how much the elevation varies within the grid) and keep our other controls. That yields an estimate virtually indistinguishable from our baseline (r=-0.6025, p=0).

The stability of the estimate under all these controls gives us good confidence than the Heliocentric theory is essentially right. Of course, the Heliocentric geometry of our lifeworld does not dictate the fate of societies. But it does structure it; quite powerfully so, as we have shown.

I know it feels vaguely racist to tie biogeography to global polarization. But the truth is that biogeography is not racist but rather an alternative to racialism as an explanatory schema for global polarization. Indeed, it is arguably less offensive than culturalist explanations. Britain has 66 million souls; India has 1,339 million. The latter has now been independent for 73 years. Yet India’s economy still smaller than Britain’s. Why?? Is it not more offensive to suggest that the reason is that the former is culturally retarded than that it faces heavier biogeographic burdens? Who is more in tension with Boas? Binfordian anthropology or post-processualism (whatever that is)?

Hegemonic Boasian antiracism has itself to blame for the rise of neoracialism. Put simply, racialism was marginalized without replacement. All the explanatory work that racialism was doing was simply left undone. No alternate explanation of global polarization was offered. It was simply assumed that convergence would obtain as nations Modernized. When that failed to obtain the door was thus left ajar for the resurrection of racialism to do the same work it had performed in the heyday of racial anthropology.

I believe in the agency of societal actors. Escape from want is definitely possible for all nations. But the problems of the low latitude nations cannot be solved by simply assuming them away. The catastrophic failure of the mid-century dream of Modernization stems precisely from that elementary mistake. Nations are situated communities. Uniform strategies imported from the northern nations, whether economic best practices or modernization theories, won’t solve their concrete problems. Indeed, it cannot be more obvious that unless low latitude nations find ways to mitigate the burdens imposed by the Heliocentric geometry of our lifeworld, they will not escape the tyranny of the isotherms.

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