Abstract
This thesis explores how genetics influences socioeconomic traits, such as education, income, and health outcomes. It contributes to the methodology of measuring the genetic underpinnings of such traits, and makes an applied contribution by assessing the role that genetics plays in the intergenerational transmission of socioeconomic status.
Chapters 2 and 3 study how the large genetic data sets that are used in genomewide association studies (GWAS) of human behavioral traits are subject to selection bias, because respondents participate in such data sets on a voluntary basis. In Chapter 2, I highlight how various estimates from a frequently used large-scale biobank (the UK Biobank) may be misleading due to volunteer bias, how this bias can be mitigated with inverse probability weights, and I give suggestions on how the next generation of biobanks could deal with this problem of volunteer bias.
In chapter 3, I use the weights estimated in Chapter 2 to show that the non-representative sampling of genetic data biases GWAS analyses. Correcting for volunteer bias using inverse probability weights generally increases the effect sizes of SNPs, increases heritability estimates and alters gene tissue expression results for various traits investigated.
In chapter 4, I study the impact of the polygenic index (PGI) for educational attainment (EA) on the socioeconomic outcomes of one's children. Studying this causal impact is made possible through a novel link between the Lifelines Cohort Study and Dutch administrative data. I condition on the sum of grandparental PGIs to isolate exogenous variation in a parent's PGI at the conception of this parent. As a result, the estimated effect of the parent's PGI on their children's outcomes can be causally interpreted. I find that the EA PGI of parents influences their children's education, income, and wealth, once these children have reached adulthood. The effects are relatively large, showing a surprisingly high intergenerational persistence of one's EA PGI. I show that this high persistence can be understood because two mechanisms mediate the effect of a parent's PGI on children's socioeconomic outcomes. The first occurs at conception of the child, due to the transmission of genetic material from the parent to the child. The second mechanism is environmentally mediated: the genes of a parent influence the environment in which children grow up. Hence, even genes that are not transmitted to the child impact socioeconomic outcomes of children. This “genetic family environment” effect is especially large for wealth-related outcomes, contributing to the large intergenerational persistence of wealth.
Original language | English |
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Qualification | PhD |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 15 Jan 2025 |
Print ISBNs | 9789036107785 |
Electronic ISBNs | 9789036107785 |
DOIs | |
Publication status | Published - 15 Jan 2025 |
Keywords
- Genomewide association Study
- Intergenerational Transmission
- Human Capital
- GWAS
- Volunteer Bias
- Social Science Genetics
- Polygenic Index
- Educational Attainment
- UK Biobank
- Lifelines Cohort Study