Does Health-related Aid Really Matter? Evidence from South Asia
Bibliographic record
Abstract
Using data from South Asia for the period 1990–2017, this paper examines the effectiveness of the health sector aid on infant mortality, neonatal mortality, child mortality and a new composite index of child mortality. The investigation of South Asia is interesting not only because it accounts for roughly one quarter of the world population and has attracted significant aid over the years but also because of the significant variations in health outcomes between countries in the region. Applying the instrumental variables method to account for the endogeneity of aid, we find that health-focused aid assists in improving child health outcomes in South Asian countries. The effect operates mainly through female literacy and is robust to a variety of specifications. Our findings have significant policy implications for achieving the post-MDG target and point to the importance of the health sector aid to improve child health for countries swamped with poorer health status. JEL Codes: F35, I15, O53
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 0.007 |
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; both teacher heads agree on what is shown here.
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".