Willingness-to-Pay for Family-Based Health Insurance: Findings From Household And Health Facility Surveys in Central Vietnam
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".