The Effects of Healthcare Quality on the Willingness to Pay More Taxes to Improve Public Healthcare: Testing Two Alternative Hypotheses from the Research Literature
Bibliographic record
Abstract
The research literature discusses two opposite hypotheses regarding the possible effects of healthcare quality on the willingness to pay more taxes to improve public healthcare. One hypothesis theorizes that a lower quality of public healthcare may weaken the willingness to pay more taxes towards improving it. Another hypothesis posits that a low quality of public healthcare may strengthen the willingness to pay more taxes towards improving it. We tested both hypotheses on a diverse sample of 27 post-communist countries within Eurasia and Southern and Eastern Europe over a period of five years. We apply a binary logistic model for each country under investigation. The model is estimated by regressing the willingness to pay more taxes on six dimensions of quality, while controlling for covariates and the dummy for 2016. We found empirical support for both hypotheses, and hence none of the hypotheses gleaned from the literature is a clear "winner." However, we also found that the situation is less straightforward and more nuanced than is usually acknowledged within the literature. Our findings also suggest the effect is specific with respect to both a quality dimension and a country tested.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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".