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Record W2562588093

Estimating the economic effects of remittances on the left-behind in Cambodia

2015· preprint· en· W2562588093 on OpenAlexfundno aff
Vutha Hing, Dalis Phann, Vathana Roth, Sreymom Sum

Bibliographic record

VenueRePEc: Research Papers in Economics · 2015
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
FundersDepartment for International DevelopmentInternational Development Research CentreGovernment of Canada
KeywordsUnobservablePovertyEmigrationSalaryEconomicsPropensity score matchingDemographic economicsConsumption (sociology)Labour economicsMatching (statistics)Left behindDependency ratioInvestment (military)Economic growthGeographyPolitical sciencePopulationEconometricsDemography
DOInot available

Abstract

fetched live from OpenAlex

Using propensity score matching with the 2009 Cambodia Socio-Economic Survey of households, this study examines the effects of remittances on indicators of household wellbeing: poverty, consumption and labour participation of non-migrant members. The theoretical framework is built upon a “new economics of labour migration”, hypothesising that the emigration decision is jointly determined by households and individual migrants and that remittances basically represent a form of contractual arrangements between them. The results indicate that households with at least one migrant member and which receive remittances could reduce their poverty headcount rate by 3-7 percentage points vis-à-vis their matched controls. Remittances also reduce depth and severity of poverty of treated households. On the contrary, remittances generate a 5-9 percent “dependency effect” on working age adults who are employed due to reduced weekly hours worked. The impact of remittances on labour participation and salary income is, however, vulnerable to unobservable factors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.033
GPT teacher head0.354
Teacher spread0.321 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2015
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicMigration and Labor DynamicsFrench-language works237,207