MétaCan
Menu
Back to cohort
Record W2896399651 · doi:10.1007/s13524-018-0716-1

Saving, Sharing, or Spending? The Wealth Consequences of Raising Children

2018· article· en· W2896399651 on OpenAlex
Michelle Maroto

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDemography · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNet worthEconomicsQuantile regressionConsumption (sociology)National Longitudinal SurveysPercentileInvestment (military)Raising (metalworking)Demographic economicsDistribution (mathematics)National wealthWealth distributionCohortDemographyInequalityEconometricsMedicineFinance

Abstract

fetched live from OpenAlex

This study uses 1986-2012 National Longitudinal Survey of Youth 1979 cohort data to investigate the relationship between raising children and net worth among younger Baby Boomer parents. I combine fixed-effects and unconditional quantile regression models to estimate changes in net worth associated with having children in different age groups across the wealth distribution. This allows me to test whether standard economic models for savings and consumption over the life course hold for families at different wealth levels. My findings show that the wealth effects of children vary throughout the distribution. Among families at or below the median, children of all ages were associated with wealth declines, likely due to the costs of child-rearing. However, at the 75th percentile and above, wealth increased with the presence of younger children but decreased after those children reached age 18. My results, therefore, provide evidence for a saving and investment model of child-rearing among wealthier families but not among families at or below median wealth levels. For these families, the costs of raising children largely outweighed motivations for saving.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.267
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it