Leakage of Public Resources in the Health Sector: An Empirical Investigation of Chad
Bibliographic record
Abstract
In the public sector in developing countries, leakage of public resources could prove detrimental to users and affect the well-being of the population. This paper empirically examines the importance of leakage of government resources in the health sector in Chad, and its effects on the prices of drugs. The analysis uses data collected in Chad as part of a Health Facilities Survey organized by the World Bank in 2004. The survey covered 281 primary health care centers and contained information on the provision of medical material, financial resources, and medicines allocated by the Ministry of Health to the regional administration and primary health centers. Although the regional administration is officially allocated 60 percent of the ministry's non-wage recurrent expenditures, the share of the resources that actually reach the regions is estimated to be only 18 percent. The health centers, which are the frontline providers and the entry point for the population, receive less than 1 percent of the ministry's non-wage recurrent expenditures. Accounting for the endogeneity of the level of competition among health centers, the leakage of government resources has a significant and negative impact on the price mark-up that health centers charge patients for drugs.
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".