Effects of Genetic Propensity for Education on Labor Market and Health Trajectories across the Working Life

2026-04-27

AI Summary

This study investigates how education-linked genetic predispositions shape long-term income and health trajectories. Leveraging 25 years of registry data on 51,065 Finnish graduates, combined with an educational attainment polygenic index (EA-PGI), intergenerational triad controls, and lifetime discounted income measures, the research reveals that high EA-PGI significantly boosts earnings only among individuals who attain higher education—those at the 90th EA-PGI percentile earn 13.1% more than those at the 10th percentile. This effect operates primarily through more frequent transitions to high-quality employers. Notably, indirect genetic effects transmitted via paternal EA-PGI dominate: controlling for fathers’ EA-PGI attenuates the income gap by 71%, challenging conventional human capital theories that emphasize direct individual genetic effects.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Humans and AI: Learning Human Values and Preferences
• Multiagent Systems: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems

Abstract

Education is a major source of inequality in income and health. Polygenic indices for educational attainment (EA-PGI) capture both direct and indirect genetic influences on education, but their effects on income and health remain unclear. Using Finnish registry data on 51,056 graduates followed annually since graduation for up to 25 years, we report three findings. First, higher EA-PGI strongly predicts income growth, but only among higher educated people: tertiary-educated graduates at the 90th percentile earn EUR 45,392 (13.1 percent) higher discounted lifetime income than those at the 10th percentile. This effect is not mediated by overall health and is entirely absent for the secondary (high school)-educated workers, who do not benefit from higher EA-PGI levels. Second, EA-PGI does not predict income differences at labor market entry or the quality of the first employer, but rather higher job-to-job mobility toward higher-quality firms that drives the long-run income divergence. Third, controlling for parental EA-PGI in 12,871 parent-offspring trios reduces the discounted lifetime income gap by 71 percent, and the effect of paternal (but not maternal) EA-PGI on offspring income exceeds that of the offspring's own EA-PGI. These findings suggest that genetic factors associated with educational attainment predict income trajectories primarily through faster and more frequent changes to higher-paying employers. However, much of this association reflects indirect paternal genetic effects, consistent with enduring paternal patterns of intergenerational job and income transmission.

Problem

• polygenic index
• educational attainment
• income inequality
• intergenerational transmission
• labor market trajectory

Innovation

• polygenic index
• intergenerational transmission
• job mobility
• lifetime income
• genetic propensity