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A country low in trust, altruism, and positive reciprocity would be “antisocial”, regardless of their patience, risk-taking, and negative reciprocity. The numbers in this table are all excluding country fixed effects, meaning that they ignore the fact that in some countries that average level of trust, altruism, and positive reciprocity are high (and in others those are low), for example. However, the numbers in Table 3 indicate that on top of those individual correlations, there is a similar pattern of variation in the average level of trust or patience (or any of the other characteristics) across countries as we see with individuals. If we take high GDP per capita, high life expectancy, and few homicides as a rough gauge of development, then developed places tend to have two traits, patience and trust, and probably tend to be risk-averse and put a high weight on negative reciprocity.

The TL;DR version of them is that I don’t find the empirical work convincing in establishing the proposition that institutions are the fundamental determinant of comparative development. That is, it implies that Liberia’s institutions (a 2) are better than Cuba’s (a 1) in exactly the same way that Australia’s (a 7) are better than South Korea’s (a 6). The second kind of question is “Are institutions responsible for sustained growth and/or comparative development? That’s the purpose of Dell’s paper on the mining mita, and the purpose of Iyer’s paper on British rule in India.

Rather than look at the density plots, the next figure shows log GDP per capita in 2010 against log GDP per capita in 1820 for the 48 countries that have data in both years. Looking down the range of GDP per capita, places like the southern cone of South America (Argentina, Chile, Uruguay) all have large groups of European descent, and they tend to be somewhat richer than places without European-descended populations, as in much of South Asia and Sub-Saharan Africa. The variation in living standards that shows up in Maddisons data in 1820 is correlated with whether a country took off to sustained growth or not after 1820, but that variation reflects the experience of colonization that took place prior to 1820 as well. Going back to AJR, they showed that among colonies, places with high urbanization rates or high population density in 1500 (e.g. North Africa, Mexico) were relatively poor in GDP per capita by 1995.

If you want to think about how this deep roots literature fits with UGT, think of it as trying to figure out the specific conditions that determine why some places hit the take-off point, and when, rather than figuring out the specific mechanics of how a take-off works. That means that within the existing data, it is quite plausible to find pairs of ethnic groups that have different patience levels today even though they had similar productivity levels, or pairs with the same patience, but with different productivity. More to the point on determinism, the results don’t mean that ethnic group A with higher productivity had to have higher patience than group B with lower productivity. The significant relationship of productivity and patience means that we’d expect patience to be higher in A than in B in more than half of those runs, but the R-squared of 10% it wouldn’t happen in all of them.