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Record W4309232698 · doi:10.1515/bejm-2021-0165

The Welfare Effects of Social Insurance Reform in the Presence of Intergenerational Transfers

2022· article· en· W4309232698 on OpenAlexaff
Jingjing Xu

Bibliographic record

VenueThe B E Journal of Macroeconomics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsThe King's UniversityWestern University
Fundersnot available
KeywordsEconomicsWelfareEarningsContext (archaeology)Social insuranceOverlapping generations modelGeneral equilibrium theorySafety netLabour economicsMicroeconomicsFinance

Abstract

fetched live from OpenAlex

Abstract Family support in the form of intergenerational transfers could serve as a substitute for the public transfer system, especially when the public safety net is weak. These intergenerational transfers could be impacted by changes in public insurance. Conversely, induced changes in family transfers could also impact the effectiveness of a public insurance program. What is the impact of social insurance reform on household welfare in the context of intergenerational transfers? This paper investigates this question by using an overlapping generations general equilibrium model where parents and their children are linked by intergenerational transfers. In the model, individuals differ in earnings ability and face idiosyncratic uninsurable income risk, health risk, and mortality risk. This paper calibrates the model to key features in the urban Chinese economy. Using this calibrated model, this paper finds that households on average experience a welfare gain from an increase in the social insurance benefits but that this effect differs across households conditional on their economic status. This paper then provides a decomposition of these welfare changes into three channels: a direct policy channel, an intergenerational-transfers channel, and a general equilibrium channel.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.007
GPT teacher head0.250
Teacher spread0.243 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

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Same venueThe B E Journal of MacroeconomicsSame topicIntergenerational Family Dynamics and CaregivingFrench-language works237,207