Genes, education, and the labor market: What genetic information can tell us about income inequality

Kevin Thom and
Kevin Thom Kevin Thom is a Clinical Associate Professor in the Economics Department at New York University. His research focuses on a range of topics in applied microeconomics including labor markets in less developed countries, health behaviors, and the intersection between biology and economic decision-making.
Nicholas Papageorge
Nicholas Papageorge Broadus Mitchell Associate Professor of Economics - Johns Hopkins University

February 29, 2016

Income and wealth inequality in the U.S. is a stark reality.  Against this backdrop, it is noteworthy that research from a variety of fields suggests strong intergenerational transmission of education and economic outcomes. Children born into poor families tend to end up less educated, less healthy, more prone to contact with the police, and less likely to accumulate wealth over the life-cycle.  In contrast, children born into well-off families tend to exhibit better outcomes on all of these dimensions.

How should social scientists and policymakers understand and address intergenerational mobility in the U.S.? This question is difficult to answer – and highly politicized.  There are diverging views on the mechanisms driving high intergenerational persistence of economic outcomes. 

One possibility is that low-ability parents are more likely to have low-ability children; essentially the “nature” hypothesis.  This could be an important mechanism in explaining why many poor parents have children who likewise grow up to be poor. 

The second important mechanism involves inefficiently low investments in the human capital of individuals born into unfavorable circumstances; the “nurture” hypothesis. For example, poor families may not have the resources to make educational and parenting investments that are needed to realize the full potential of their children. If the second mechanism plays a role, then there is a clear rationale for interventions that support children in poor families. Indeed, it may even be the case that policies correcting under-investments in human capital are economically efficient.

However, questions about intergenerational mobility are difficult to answer.  It is not clear which of the two mechanisms dominates, i.e., to what degree intergenerational transmission of economic outcomes reflects the transmission of ability or under-investments in human capital.

Using genetic information to measure ability endowments offers one path forward in this debate.  Researchers have typically used measures such as IQ scores to track such ability endowments.  Yet, these alternative measures are subject to the critique that they in part reflect a child’s environment or earlier investments in their human capital.  Genetic information presents a clear advantage because it is fixed at conception and allows us to draw conclusions about how children with the same ability endowments fair when faced with different childhood environments.

The sequencing of the human genome and very recent advances in behavioral genetics research now make it possible to link genes to a host of economic behaviors and outcomes.  These new discoveries have even extended to educational attainment, which was once thought to be too complicated and removed from direct biological processes for genetic analysis.

In a recent research paper, [BS1] we use genetic information to better understand the nature of intergenerational mobility.  We follow the cutting edge in behavioral genetics research, which guides us in computing a type of genetic “score” for any individual.  The score, which appears to capture cognition, academic ability and a facility with learning, exhibits a degree of predictive power for educational attainment that is unprecedented for other complex economic outcomes.  We compute the genetic score for a sample of over 8,000 individuals from the Health and Retirement Study (HRS), which also contains detailed information on education and labor outcomes including employment, wages, occupation, job tasks, retirement, and wealth.

Using the genetic score, we believe we can gain new insights about how ability endowments interact with an individual’s environment to generate economic outcomes.  For example, there are long-standing debates in the economic literature about how ability and investments complement one another.  Our evidence is similar, but more nuanced.  We show that ability (measured by genes) and the environment (measured by parents’ socioeconomic status or SES) can substitute one another for lower levels of educational attainment such as a high school degree, but complement one another for higher degrees, such as college completion.  In other words, our findings suggest that ability or being born into a well-off family are enough to get through high school.  For college, however, ability and a well-off family are important predictors of success.

Another set of results concerns the growth of wage inequality over the past quarter century.  One idea popular in economics is that the ongoing rise in inequality may be driven in part by “skill-biased technological change.”   As new technologies arrive and transform the workplace, they tend to disproportionately benefit those with the skills required to adapt to and master new ways of working.   We find evidence that the gap in wages between those with higher vs. lower values of the genetic score has grown over time.  Separate analysis suggests that the genetic score is predictive of job characteristics such as the use of computers.  Together, these findings suggest that those with higher values of the genetic score might have adapted more easily to the advent of information technologies. We believe this is the first evidence on how genetic diversity interacts with skill-biased technological change.

Of course, one must be very cautious when interpreting any gene association.  In particular, it is important to think carefully about correlation versus causality.  The same parents that pass along favorable genetic material are also more likely to have the resources to invest in their children.  Still, this is an interpretational challenge that arises only if these genes also have an association with parental outcomes and resources in the first place.  In the paper, we discuss these issues in further detail and argue that genetic data still provide useful variation even given these concerns.  

New data on genetic variants present a powerful way to uncover policy relevant insights about education.  Genetic information can help us to learn about some of the complex ways in which ability endowments and environments are linked to educational attainment.  Our analysis offers some suggestive results about which environments are associated with lost potential for different ability levels. Acute negative events like physical abuse in childhood can lead to a dramatic loss of economic potential – reducing financial wealth in late adulthood for the highest ability individuals by over 50 percent.  More broadly, we find that children from lower SES backgrounds systematically acquire less education when compared to similarly capable individuals (measured by genetics) from high SES backgrounds.  Among other things, this suggests that access to education may be an important obstacle, even for the highest ability children.

By using genetic information to compare individuals from different socioeconomic backgrounds, we offer clear evidence that these educational disparities are not solely due to an intergenerational transmission of ability (e.g., the argument that low SES parents are also low ability parents).  Moving forward, as we learn more about why specific genes are associated with better educational and economic outcomes, it may become possible to design policies that more effectively develop skills for people with different ability endowments. 

Editor’s Note: The authors contributed equally to this posting and to the research upon which the posting is based.