Understanding how inherited traits, socioeconomic environments, and human capital investments interact to influence a person’s life outcomes, such as what sort of job they take or how much they earn, has long been of interest to economists. But understanding the complex ways these assets interact has historically been challenging, as their effects are hard to parse out separately. Skills and ability can also be notoriously hard to observe and measure.
In their recent HCEO working paper, MIP/HI network member Kevin Thom and HI network member Nicholas Papageorge shed some light on the ways in which a person’s genetic variation is associated with human capital accumulation and labor market outcomes. Combining data from the Health and Retirement Study (HRS) and genetic markers constructed from “Gene Discovery and Polygenic Prediction from a 1.1-Million-Person GWAS of Educational Attainment,” a paper by Lee et al. (2018), the authors use an individual’s polygenic score to predict educational attainment. A polygenic score is an index of genetic markers that aggregates together genes that influence traits specific to human capital accumulation. It is drawn from genome-wide association studies (GWAS) methodology, which scans the entire genome to find sites associated with a particular trait. More specifically, the authors examine whether childhood environments interact with genetic endowments in determining educational outcomes, and whether those endowments are associated with economic outcomes beyond their relationship with completed schooling.
“I think what Nick and I really tried to do is ask, ‘What can we as economists, potentially learn about human capital accumulation from having the results from this GWAS study?’” Thom says. “That is something that is important to us. We can go back and revisit a whole lot of classic questions in economics that we just simply couldn’t answer in very good detail without advances in measuring genetic factors that predict human capital accumulation.”
The paper presents two main sets of results. The first shows evidence that the genetic factors measured by this score interact strongly with childhood socioeconomic status in determining educational outcomes. (Note: for the purposes of this paper, the authors looked exclusively at males of European descent.) Using the HRS data, the authors are able to “replicate the strong relationship between the genetic score and educational attainment found in past studies.” They find that variation in the polygenic score accounts for up to 9.7 percent of variation in years of schooling. Interestingly, the distribution of scores was similar across all SES groups, making it possible to compare economic outcomes for individuals with similar genetic scores but different childhood environments. The authors note that while the polygenic score predicts higher rates of college graduation on average, this relationship is substantially stronger for individuals who grew up in households with higher socioeconomic status relative to those who grew up in poorer households.
“That’s quite interesting because it suggests two things,” Thom says. “One is that environments are potentially interacting with genetic endowments, and can complement whatever it is that these genetic endowments do for an individual. The second takeaway that I think is really big is that there seems to be wasted human potential. There’s a whole bunch of people with high polygenic scores, and high genetic propensities for acquiring human capital that don’t seem to be getting college degrees at the same rates as individuals who were born into high-SES families. It really does seem like there’s an environmental bottleneck.”
The second result shows that the polygenic score predicts labor earnings even after controlling for completed education, with larger returns in more recent decades, coinciding with the rise in income inequality after 1980. A one-standard-deviation increase in the polygenic score is associated with a 4.5 percent increase in earnings after 1980. The authors also find a positive association between the score and non-routine job tasks that benefited from more advanced information technologies. “These patterns suggest that the genetic traits that promote education might allow workers to better accommodate ongoing skill-biased technological change,” the paper notes.
While the authors find that individuals with high polygenic scores across education backgrounds benefited from new technologies, the college premium remains significant. “Importantly, the genetic gradients in both earnings and job tasks are roughly similar for individuals with and without a college degree,” the authors write. “This suggests that high-educational attainment individuals without a college degree do not find ways to easily sort into jobs with tasks that heavily complement new technologies. Genetic endowments do not compensate for a lack of a college degree in the labor market.”
The authors admit that their results could still be influenced by environments or investments not captured by the HRS study. Individuals with higher values of the polygenic score necessarily have birth parents with high values, “making it difficult to determine how much of the associations we estimate arise from the biological traits linked to these genetic markers, or to the positive environments provided by their parents.” Even so the findings stress the importance of fostering human capital accumulation, particularly as returns to education continue to increase.
“If we live in a world where the skills or abilities associated with the polygenic score are rewarded at higher and higher rates, you would really want to know how easy it is for kids born with high polygenic scores to reap those rewards,” Thom says. “That’s obviously of great importance for them individually, but it’s also a question of great importance for the economy overall. We have a human resource in the form of these genetic endowments. It's important for us to know whether those endowments are getting paired up with the right educational investments, and whether there are roadblocks that prevent that process from being socially optimal in terms of the formation of human capital.”
Thom also notes the importance of this study for future research. “What is it that differentiates a child that has a high polygenic score from a child that has a low polygenic score?” he asks. “Right now it’s a bit of a black box. We know very few things about the underlying biological or behavioral mechanisms through which these genes operate. Shedding some light on that is going to also help us look at policy, because we might have some sense of how to intervene to maximize opportunity for everybody.”