|Integrating Genetics into Economics
|Year of Publication
|Economics, Entrepreneurship, Genetics, Mental Health, Polygenic risk scores
The massive increase in sample size of genetic cohorts, combined with an increase in the collection of data on social-scientific outcomes in these datasets, has made it possible to study many socio-economically relevant individual characteristics from a genetics perspective. In economics, the subfield that studies the genetic architecture of socioeconomic outcomes and preferences is often called genoeconomics. Ultimately, genoeconomics can help economics in four different ways: genes can be used as measures of previous latent variables, genes can uncover biological mechanisms, genes can be used as control variables or instrumental variables, and genes can be used to target policy interventions. In this thesis, I develop and compare some methods that can be used in genoeconomics, and I show through empirical studies how genetically informed study designs can give new insights to economists. The methods developed and compared in this thesis foster the use of genes as instrumental variables and help further the understanding of genetic relationships across socio-economically relevant characteristics. The main empirical applications in this thesis concern smoking behaviour, entrepreneurship, and the structure of the brain. This first chapter provides an overview of the thesis, including a discussion of the research questions it addresses and the implications resulting from the answers to these questions.