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Record W4414077554 · doi:10.1007/s11150-025-09804-2

Health shocks and household allocation of time and spending

2025· article· en· W4414077554 on OpenAlexafffund
Federico Zilio, Ross Hickey, James Ted McDonald, Eric Sun, Yuting Zhang

Bibliographic record

VenueReview of Economics of the Household · 2025
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversity of New BrunswickUniversity of British Columbia, Okanagan Campus
FundersAustralian Research CouncilSocial Sciences and Humanities Research Council of CanadaAustralian Government
KeywordsSpouseShock (circulatory)Life expectancyConsumption (sociology)Household incomeWorkforceSurvey data collectionAlcohol consumptionBritish Household Panel Survey

Abstract

fetched live from OpenAlex

Abstract How do household spending and time use respond to health shocks? Secular increases in the incidence of dual earning couples, the aging of the workforce and higher life expectancy make this question particularly relevant for economists and policymakers. We use Australian data from the Household Income and Labour Dynamics Survey to study this question. Using an event study design, we show that the labor supply of those that experience a health shock decreases from their baseline for more than a year. Home production increases for the spouse of the ill person in two dimensions: increased time spent caring for household members and increased time spent on household chores. We also find that households spend more money on household and medical items and less on holidays and alcohol in response to the health shock. Although household income only moderately decreases, the inability to cut total spending results in a higher proportion of individuals reporting financial stress. We discuss our findings in relation to the provision of social insurance in advanced economies.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.065
GPT teacher head0.382
Teacher spread0.318 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations3
Published2025
Admission routes2
Has abstractyes

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