Essays in Social Economics

This dissertation explores the roles of nature and nurture in shaping social, economic, and health outcomes. It examines their relative contributions to economic preferences and outcomes, how genetics can amplify or dampen the effects of economic shocks, and how genetic prediction technology can shape precision medicine efforts in breast cancer screening and other diseases. The contribution of this study is to further enhance the understanding of how genetic and environmental influences, separately and in combination, affect our economic and social lives.

 

In the first essay, I directly study nature and nurture using random variation in the genetic relatedness of sibling pairs. A consequence of Mendel's First Law is that siblings' genetic relatedness varies randomly (with a mean of 50% and a standard deviation of ~ 3.5\%). We use molecular genetic data to compute the genetic relatedness of roughly 80,000 sib pairs. We then compare the pairs' genetic relatedness to their similarity on a suite of 15 traits in the labor market, cognitive and educational, risk taking, health, and anthropometric domains, to obtain estimates of the outcomes' heritabilities. We find evidence of sizeable genetic influences on several traits, including risk tolerance, subjective wellbeing, fertility, cognitive performance, height, and BMI, as well as evidence of common environment influence for occupational and family income, occupational status, educational attainment, smoking behavior, drinks per week, and general health.

 

In the second essay, I test for the existence of gene-by-environment interactions between local labor market conditions and polygenic risk scores, which are trait predictors constructed with an individual’s molecular genetic data, for an array of health and wealth traits. I use information from several digitized censuses to construct a Bartik instrument for labor demand in the county and year of birth of a sample of genotyped British citizens, which serves as an exogenous economic environment component. I find that polygenic scores enhance the effect of economic shocks for female education, male birth weight, and male systolic blood pressure, and dampen the effects of these shocks for female systolic blood pressure.

 

In the third essay, I implement an econometric package, which will be made publicly available, to correct maximum likelihood models for measurement error in polygenic risk scores and demonstrate its utility by examining how future, more predictive, polygenic risk scores will affect screening in the UK’s National Health Service for a suite of major diseases.  I find that if polygenic risk scores become predictive enough to explain a proportion of breast cancer variance equal to twin heritability, then the number of women eligible for early screening under the NHS’s current rules may increase as much as 7 times.