Price Competition in the Chinese Pharmaceutical Market
Bibliographic record
Abstract
Previous economic studies on pharmaceutical price competition found wide variations across major developed countries. In the mostly free-pricing US, the price of originator products remains unchanged or even rises slightly in response to generic competition, while the price of generic products decreases with more generic entries and presumably moves toward the marginal cost of production (for example, see Caves, Whinston and Hurwitz, 1991, Grabowski and Vernon, 1992, and Frank and Salkever, 1997). Consequently, generics typically account for the bulk of molecule sales shortly after patent expiration in the US. In an extensive cross-country comparison, Danzon and Chao (2000) found that generic competition leads to lower prices in unregulated or less regulated countries such as the US, the UK, Canada, and Germany but is ineffective in countries with strict price regulation such as France, Italy, and Japan. However, their evidence on therapeutic competition, i.e., between products of similar molecules in the same class, is less conclusive due to selection biases associated with entry decisions (Danzon and Chao, 2000).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".