That new paper by Daniel Barth, Nicholas W. Papageorge and Kevin Thom is attracting a great deal of attention and also some controversy. Here is the first sentence of the abstract:
We show that genetic endowments linked to educational attainment strongly and robustly predict wealth at retirement.
But it’s not mainly about IQ. I found this to be the most interesting part of the paper, noting that EA is a polygenic score:
Our use of the EA score as a measure of biological traits linked to human capital is related to previous attempts in the literature to measure ability through the use of tests scores such as IQ or the AFQT…We note two important differences between the EA score and a measure like IQ that make it valuable to study polygenic scores. First, a polygenic score like the EA score can overcome some interpretational challenges related to IQ and other cognitive test scores. Environmental factors have been found to influence intelligence test results and to moderate genetic influences on IQ (Tucker-Drob and Bates, 2015). It is true that differences in the EA score may reflect differences in environments or investments because parents with high EA scores may also be more likely to invest in their children. However, the EA score is fixed at conception, which means that post-birth investments cannot causally change the value of the score. A measure like IQ suffers from both of these interpretational challenges. High IQ parents might have high IQ children because of the genes that they pass on, but also because of the positive investments that they make…Compared to a cognitive test score like IQ, the EA score may also measure a wider variety of relevant endowments. This is especially important given research, including relatively recent papers in economics, emphasizing the importance of both cognitive and non-cognitive skills in shaping life-cycle outcomes (Heckman and Rubinstein, 2001). Existing evidence suggests a correlation of approximately 0.20 between a cognitive test score available for HRS respondents and the EA score (Papageorge and Thom, 2016). This relatively modest correlation could arise if both variables measure the same underlying cognitive traits with error, or if they measure different traits. However, Papageorge and Thom (2016) find that the relationship between the EA score and income differs substantially from the relationship between later-life cognition scores and income, suggesting that the EA score contains unique information…
…we interpret the EA score as measuring a basket of genetic factors that influence traits relevant for human capital accumulation.
If I understand the paper correctly, the polygenic score is what predicts well from the genetic data set, it is not a “thing with a known nature.” And I believe the results are drawn from the same 1.1 million person data set as is used in this Nature paper.