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Record W3022135611 · doi:10.3386/w21101

Child Cash Benefits and Family Expenditures: Evidence from the National Child Benefit

2015· report· en· W3022135611 on OpenAlexaffabout
Lauren Jones, Kevin Milligan, Mark Stabile

Bibliographic record

VenueNational Bureau of Economic Research · 2015
Typereport
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsCashEconomicsPublic economicsMonetary economicsFinance

Abstract

fetched live from OpenAlex

A vast literature has examined the impact of family income on the health and development outcomes of children. Income may improve child outcomes through two mechanisms. First, income may improve development outcomes if it improves a family's ability to purchase direct inputs into child education and health production such as reading material, educational equipment, and health care. Second, by reducing stress and conflict, additional income helps to foster an environment more conducive to healthy child development, regardless of the nature of specific expenditures. In this paper, we exploit changes in refundable tax benefit income in Canada to study these questions. Importantly, our approach allows us to make stronger causal inferences than has been possible in existing studies. Using variation in child benefits across province, time, and family type, we study expenditure patterns of families receiving child benefits. Our findings suggest that additional income may improve outcomes through both mechanisms: some benefit income is spent on direct education and health inputs, while some is spent on everyday items likely to improve the general conditions children face. Additionally, some families reduce spending on risky behavior items. Spending responses to benefit generosity appear to vary by income.

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.

How this classification was reachedexpand

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)0.014
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.359
GPT teacher head0.483
Teacher spread0.125 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations52
Published2015
Admission routes2
Has abstractyes

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