The Impact of Decentralization on the Provision of Public Health Insurance Evidence from Canadian Formulary Adoption Decisions
Bibliographic record
Abstract
This paper studies fiscal federalism in the context of public health insurance. Specifically, we study how provincial governments in Canada decide on what pharmaceuticals to cover as part of their provincial health plans (i.e their formularies) using a unique panel on province-drug adoption decisions, for 1200 drugs from 1993-2008. We develop and estimate a dynamic model of provincial drug adoption that accounts for province-specific tastes for dierent therapeutic classes of drugs, and sunk adoption costs required for drug listings. Our model allows for the possibility of strategic delay in adoption decisions, which arises if adoption costs are declining in the number of provinces that adopt a given drug. We estimate the model using recent innovations in the estimation of dynamic games developed by Aguirregabiria and Mira (2007). The estimated model is used to evaluate two important healthcare policies. First, we evaluate the impact that the Common Drug Review, a national institution that is founded in 2003 to perform experimental evaluations of new drugs on behalf of the provinces (with the exception
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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 | 0.006 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".