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Record W2071113445 · doi:10.1177/1091142113515053

Fiscal Incidence When Family Structure Matters

2014· article· en· W2071113445 on OpenAlexaffabout
Haizhen Mou, Stanley L. Winer

Bibliographic record

VenuePublic Finance Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsCarleton UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsEconomicsSubsidyAllowance (engineering)Incidence (geometry)PopulationWelfarePublic economicsOrder (exchange)Tax incidenceDemographic economicsMicroeconomicsDemographyFinanceOperations management

Abstract

fetched live from OpenAlex

Population aging has led to demands for subsidization of home care for the elderly, and many countries now provide such help. In this article, we investigate analytically and with simulation the fiscal incidence of a cost-sharing price subsidy for home care. Our focus is on incidence and benefit shifting between elderly parents and their children who provide time or money. We first derive incidence indexes on a budgetary and on a welfare basis. We then simulate our indexes using Canadian data in order to understand how incidence actually depends on basic family structure, the nature of altruism, and other key factors. Finally, we simulate the implications for fiscal incidence of a switch from a price subsidy to a lump-sum allowance that allows the family somewhat greater freedom of choice. The article concludes with reflections on the general state of expenditure incidence analysis.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.277
Teacher spread0.254 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2014
Admission routes2
Has abstractyes

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