Revenue Structures, The Perceived Price of Government Output, and Public Expenditures
Bibliographic record
Abstract
This article examines how revenue structures, through fiscal illusion effects, influence government spending. It does so with a regression model in which public spending depends on the perceived price of public services and other demand variables. The authors construct a perceived price term that provides a more general framework for testing together several hypotheses of fiscal illusion. The perceived price depends on public revenues, decomposed into nine revenue sources, and is a weighted average of how fully taxpayers recognize the cost of each revenue source. For a sample of the 10 Canadian provinces from 1961 to 1992, the authors find that revenue structures influence spending, that tax revenues are perceived more acutely than other major revenue sources (borrowing, grants), and that some taxes are recognized more than others. The results can be viewed as consistent with debt illusion, flypaper, and income-elastic versions of fiscal illusion while casting doubt on using the Herfindahl index to represent fiscal illusion. The authors also find learning by taxpayers (declining fiscal illusion) during the period.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".