Are user charges efficiency‐ and equity‐enhancing? A critical review of economic literature with particular reference to experience from developing countries
Bibliographic record
Abstract
Abstract User charges have come to play a significant role in the financing and delivery of publicly provided health services in many developing countries. As a response to health care financing crises, user charges are often promoted as a way of rationalizing the use of care, raising revenue, and improving the coverage and quality of services. The primary purpose of this paper is to provide a critical review of the main arguments for the efficiency‐ and equity‐enhancing potential of user charges. The extent and scope of welfare gains from user charges are found to be very limited in practice. Using a less restrictive theoretical choice model and estimation technique, the most recent demand studies' findings indicate that household's utilization of health services are more responsive to changes in price and income than was initially reported by the early demand studies. Response to price changes are also found to be greater among the poor than the rich. These findings, combined with modest retained fee revenues and the failure of exemption mechanisms to protect the poor tend to cast doubt on the net benefits of user charges policy, particularly in the area of equity. Copyright © 2001 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".