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Record W4384665681 · doi:10.1111/caje.12666

Can I live with you after I retire? Retirement, old age support and internal migration in a developing country

2023· article· en· W4384665681 on OpenAlexvenueno aff
Simiao Chen, Zhangfeng Jin, Klaus Prettner

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
FundersNational Office for Philosophy and Social SciencesBill and Melinda Gates Foundation
KeywordsInternal migrationRegression discontinuity designPensionDemographic economicsAccommodationGovernment (linguistics)Developing countryRetirement agePopulation ageingSample (material)EconomicsOld Age SecurityPopulationDemographyEconomic growthMedicinePsychologySociologyBirth rateFinanceResearch methodology

Abstract

fetched live from OpenAlex

Abstract This study provides causal evidence on the impact of retirement on internal migration in a developing country. Using a fuzzy regression discontinuity design, combined with a nationally representative sample of 228,855 older Chinese adults, we find that retirement leads to an increase in the probability of being a migrant by 12.9 percentage points (an 80% increase in migration). Approximately 38% of the total migration effects can be attributed to intertemporal shifts. The impact is more pronounced for the lower‐educated, those who have restricted access to health insurance and pension and those who come from origins with high accommodation costs. Relying on old age support from adult children in migration is a likely mechanism. Lifting migration restrictions and improving government‐provided benefits for retirees could be helpful to cope with population aging in a developing country.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.072
GPT teacher head0.210
Teacher spread0.138 · 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 designObservational
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

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Economics/Revue canadienne d économiqueSame topicMigration, Aging, and Tourism StudiesFrench-language works237,207