The Impact of Price-cap Regulations on Exit by Generic Pharmaceutical Firms
Bibliographic record
Abstract
BACKGROUND: In 1998, the Province of Ontario in Canada adopted price-cap "70/90" regulations whereby the first generic entrant was required to be priced at ≤70% of the associated brand-name product and subsequent generics were priced at ≤90% of the first generic price. The price-caps were further lowered to 50% in 2006 and 25% in 2010. This study assessed the impact of such price-cap regulations on exit by generic drug firms. METHODS: Formulary (2003-2012) listings of prescription drugs covered under the Ontario Drug Benefit program were used. The formulary tracks the "status" (on formulary, discontinued by manufacturer, and delisted for other reasons) for each drug. Markets were defined based on unique active ingredient and form within Ontario. Firm exit occurred when a manufacturer discontinued all its generic drugs within a market. The exit rate was defined as the number of generic firm-market exits divided by total generic firm-market follow-up years. Poisson regression was used to compare the exit rates during the 3 policy periods ("25," "50," and "70/90"). RESULTS: A total of 1126 generic manufacturers paired with 290 markets were identified. The exit rate ratio during the 25% price-cap period compared with the 70%/90% period was 2.42 (95% confidence interval, 1.56-3.77). A small manufacturer or a manufacturer in a market with ≥3 competitors or in an older market was more likely to exit. CONCLUSIONS: Lowering the price-cap level is associated with a higher incidence of generic firm exit from markets. Continuously reducing price-caps may have the unintended consequence of forcing generic firms to exit.
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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 | 0.000 | 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 | 0.000 | 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) | 0.003 | 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 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".