Distributional Effects of “Needs-Based” Drug Subsidies: Regional Evidence from Canada
Bibliographic record
Abstract
Canadian provincial government drug subsidy programs have recently begun to change the basis of subsidy from age (age 65+) to financial need (defined as high drug costs relative to income, regardless of age), in an attempt to improve the distributive equity of their programs. Little is known about the extent to which these changes are meeting equity objectives. We therefore investigate the effects of these policy changes on prescription drug expenditure burdens experienced by households of varying levels of affluence, residing in different jurisdictions. Specifically, we use data from a national household expenditure survey, conducted periodically from 1969 to 2004, and nonparametric estimation techniques which allow for the estimation of the impact of age, affluence and other covariates on the 75th, 85th and 95th quantile prescription drug budget shares without imposing the functional form restrictions typical of linear regression. Conditional quantile estimation allows us to assess the impact of the policy changes on the drug expenditure burdens of those with particularly high drug budget shares - it is these households who are the intended beneficiaries of the program changes. We find little evidence that the recent reforms have been particularly redistributive.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".