Paper link is here https://t.co/sMNe9EFRrZ

I recently went on the @lightinspires podcast, which was a lot of fun. Check it out below.

Very good summary of some of our findings from Steve Sailer.

@RichardHanania I will be honest. It appears you read the first tweet in a thread with lengthy, nuanced discussion of your question, and leapt to a midwit "correlation doesn't equal causation" take. I am happy to be proven wrong, and that you've actually read and thought about what we wrote.

Understanding what is driving the relations we document is of considerable social importance, as these are some of the biggest demographic changes of our era. The full paper can be found here: https://t.co/u9z4scEeiV /End

Overall, we think that these results are sufficiently strong to indicate that there is likely some fundamental tension between higher racial diversity and lower birth rates. 42/N

Immigrants typically move from areas where they're part of the racial majority to places where they're a minority. This shift in racial share could explain the observed fertility decline across generations, independent of cultural assimilation. 41/N

Our study also gives a new perspective on the prior finding that immigrants from high-fertility countries tend to converge to lower native fertility levels over time. While cultural transmission has been the primary explanation, our results suggest an alternative mechanism. 40/N

There’s obviously a lot more work to be done, and open questions as to what all the drivers of the effect are, especially across countries. Homophily and social trust seem to be part of the story, but there are probably other drivers too. 39/N

That said, the international results don’t tell a clear story of what’s driving the differences. El Salvador and Ecuador have patterns like the US, Uruguay and Brazil go the other way. South Africa has strong results in the US direction, Jamaica is mostly zero. 38/N

For instance, they have categories of “brown” and “indigenous”, and the question of who is in which category differs from US notions. But this is part of the point – if homophily is the driver, then how people think of themselves will change the effect. 37/N

The strongest counterexample to our theory (that we can test) is actually not Japan, but Brazil. There, areas with higher diversity are robustly associated with *higher* birth rates. It’s worth noting that their definitions and ideas of race are quite different from the US. 36/N

Even for the time series (where our predictions are weaker and more circumstantial), the idea that “higher diversity is predicted to lower birth rates” is very different from “all declines in birth rates are due to higher diversity” (which is surely false). 35/N

Third, the simplest answer is that Japan’s time series decline in birth rates is probably driven by other factors. 34/N

Second, remember that our main prediction is about the cross section, not the time series. That is, “Does a Japanese woman in a highly Japanese town have more children than a Japanese woman in a town with more immigrants?” Maybe! We would need to test. 33/N

One question we’ve gotten – what about countries like Japan and South Korea, where birth rates have declined a lot, but which are quite racially homogeneous? There’s a few answers here. The boring one is we don’t have race data for them, sadly. 32/N

We find that the increase in diversity explains 44% of the decline in birth rates since 1971, and 88% of the decline since 2006. This is a potentially very large effect. In particular, the recent declines are very hard to explain with standard drivers of fertility. 31/N

It goes without saying that with overall time series changes, it’s very hard to get any identification. The results here are only credible, if at all, because of the much sharper cross-sectional tests. But still, does diversity have enough bite to explain what we see? 30/N

Finally, can the rise in diversity explain the overall decline in birth rates? Nearly all the evidence we look at is cross-sectional – comparing two people within the same area at the same time. Here, we want to look at the time series of births in general. 29/N

The tests here aren’t nearly as tight as for homophily. But the main predictions are born out – higher trust areas have more children, and adding in measures of trust reduces the effect of race share by 20-37%. 28/N