Love and Money: Intergenerational Mobility and Marital Matching on Parental Income
Bibliographic record
Abstract
This paper makes use of matched tax-return data for daughters, their parents, their partners and their partners' parents to investigate the interactions between intergenerational mobility and marital matching for young couples in Canada. We show how assortative mating contributes to intergenerational household income persistence. The strength of the association between sons-in-law's income and women's parental income means that the intergenerational link between household incomes is stronger than that found for daughters' own incomes alone. This is also the case when viewed from the other side, so that daughters' and their partners' earnings are related to partners' parental income. These results indicate that assortative matching magnifies individual-level intergenerational persistence. In the second part of the paper we consider assortative mating by parental income. We find that daughter's parental income has an elasticity of almost 0.2 with respect to her partner's parental income. This association is of approximately the same magnitude as the intergenerational link between parents' and children's incomes. We investigate variations in the correlation between the parental incomes across several measured dimensions; cohabiting couples have lower correlations, as do those who form partnerships early, those who live in rural areas and most interestingly, those who later divorce. We interpret this last result as evidence that, on average, couples with parental incomes that are more similar enjoy a more stable match.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".