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Record W2804257520 · doi:10.5539/gjhs.v10n7p24

Willingness-to-Pay for Family-Based Health Insurance: Findings From Household And Health Facility Surveys in Central Vietnam

2018· article· en· W2804257520 on OpenAlexvenueno aff
Yasuharu Shimamura, Midori Matsushima, Hiroyuki Yamada

Bibliographic record

VenueGlobal Journal of Health Science · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceĐại học HuếVlaamse Interuniversitaire Raad
KeywordsWillingness to payPer capitaBusinessContingent valuationSample (material)Health insuranceSocioeconomicsActuarial scienceValuation (finance)Affect (linguistics)Health careDemographic economicsEnvironmental healthEconomic growthEconomicsMedicineFinancePsychologyPopulation

Abstract

fetched live from OpenAlex

This study explores factors associated with people’s willingness-to-pay (WTP) for family-based health insurance covering the whole family in central Vietnam. The amount of WTP was elicited by using a contingent value method in 2014 and the mean WTP was 2.27 percent of GDP per capita. Firstly, our study reveals that even the poor are willing to pay towards obtaining health insurance. Secondly, our regression analysis shows that the health insurance status of the household head, in addition to education, wealth level, and family size, is associated with WTP. Furthermore, our estimation results with restricted sample households whose designated health facility is the commune health station (CHS) confirm that healthcare service quality measures designed based on patients’ past experiences at the CHS are significant predictors of WTP as they can affect people’s valuation of the benefit of the health insurance.

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)0.021
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.096
GPT teacher head0.323
Teacher spread0.227 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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