The determinants of municipal tax rates in British Columbia
Bibliographic record
Abstract
In this paper we study the regional pattern of municipal business property tax rates in the province of British Columbia. Reduced‐form tax‐setting equations produce some evidence that municipal governments respond to tax changes in neighbouring jurisdictions. A joint investigation of the determinants of tax base and municipal taxation decisions, however, reveals that it is difficult to interpret this response as arising primarily out of competition over tax base. There is also some evidence that municipal tax rates are sensitive to taxes set on the same base by super‐municipal bodies. JEL Classification: C33, H71 Les déterminants des taux d'imposition municipale en Colombie Britannique. Dans ce mémoire, les auteurs étudient le pattern régional des taux d'imposition municipale sur la propriété foncière commerciale dans la province de la Colombie Britannique. On montre à l'aide d'un modèle en forme réduite d'équations de définition des taux d'imposition que les gouvernements municipaux réagissent aux changements dans les taux d'imposition dans leur voisinage. Cependant, un examen conjoint des déterminants de la base d'imposition et des décisions municipales montre qu'il est difficile d'interpréter cette réaction comme émanant d'une concurrence fiscale. On montre aussi que les taux d'imposition municipale sont sensibles aux niveaux de fiscalité imposés sur la même base par les autorités supra‐municipales.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".