Rich States, Poor States: Assessing the Design and Effect of a U.S. Fiscal Equalization Regime
Why this work is in the frame
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Bibliographic record
Abstract
Unlike most of the world’s federations – including Australia, Canada, Germany, India, South Africa and numerous others – the United States has no system of federal equalization grants in place to reduce fiscal disparities among its subnational governments. Only at the state level, through policies designed to mitigate property tax disparities among school districts, has equalization been tried in the United States. The federal government has never adopted, nor has it ever seriously considered, an equalization policy for the states. This article represents the first comprehensive scholarly treatment of a possible U.S. fiscal equalization regime. It reviews the most recent data relating to fiscal disparities among the U.S. states and reports the results of simulations showing the overall cost and distributive effects of adopting a Canadian-style equalization regime in the United States. Two alternative policies are examined, one based on the “representative tax system” methodology employed in Canada and a second, known as the “representative revenue system,” that employs a slightly broader measure of state fiscal capacity. Depending on the methodology employed, the cost of a U.S. equalization policy (based on 2005 data) would be in the range of $70-$110 billion per year, or roughly 1 to 1.5 times the annual cost of the current income tax deduction for state and local taxes. Under both methodologies, as well as alternative formulas adjusting for regional cost-of-living differences, the principal beneficiaries would be the so-called “red states” of the South. On a per capita basis, the main winners of a U.S. equalization policy would be Mississippi, Arkansas, and West Virginia. In terms of absolute payments, the largest beneficiary is by far Texas, accounting for approximately 15 percent of total equalization payments. The article considers arguments for and against adoption of an equalization policy and offers some preliminary comments on the politics of fiscal equalization in the U.S. context.
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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 | 0.004 | 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) | 0.000 | 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 it