Procurement institutions and essential drug supply in low and middle-income countries
Bibliographic record
Abstract
International procurement institutions play an important role in drug supply. We study price, delivery, and procurement lead time of drug products for major infectious diseases (antiretrovirals, antimalarials, antituberculosis, and antibiotics) in 106 developing countries from 2007-2017 across procurement institution types. We find that pooled procurement lowers prices: pooling internationally is most effective for small buyers and concentrated markets, while pooling within-country is most effective for large buyers and unconcentrated markets. Pooling can reduce delays, but at the cost of longer anticipated procurement lead times. Finally, pooled procurement is more effective for older drugs, compared to patent pooling institutions that target newer drugs. Our findings are robust to alternative fixed effects specifications, instrumental variable estimation, selection-on-unobservables tests, and additional analyses accounting for heterogeneity in demand elasticities across buyers and interactions with major global health initiatives.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".