Measuring family (dis)advantage: Lessons from detailed parental information

This paper provides new insights on the importance of family background by linking 1.7 million Dutch children's incomes to an exceptionally rich set of family characteristics - including income, wealth, education, occupation, crime, and health. Using a machine learning approach, I show that conventional analyses using parental income only considerably underestimate intergenerational dependence. This underestimation is concentrated at the extremes of the child income distribution, where families are often (dis)advantaged across multiple dimensions. Gender differences in intergenerational dependence are minimal, despite allowing for complex gender-specific patterns. A comparison with adoptees highlights the role of pre-birth factors in driving intergenerational transmission.