How Should the United States Treat Government Entities, Nonprofit Organizations, and Other Tax Exempt Bodies Under a VAT?
Bibliographic record
Abstract
Goods and services supplied by government entities, public sector bodies, nonprofit organizations, charitable organizations, and similar tax-exempt bodies (the PNC sector) are usually exempt under VAT. While there are very few conceptual arguments against the full taxation of such supplies under VAT, concerns around social objectives and income distributions are often mentioned in defense of the exemption. This article reviews the case for exemption as well as its economic effects. Lessons for the United States include: (i) the case for full taxation of the PNC sector under VAT is strong; (ii) the Australian-New Zealand model would offer the best practical method to apply VAT to the sector; and (iii) to address the issue of states as taxable persons, a US federal VAT should provide states and local governments with a voluntary option to collect tax. The suggested design would result in the lowest efficiency costs, and likely the lowest compliance and administrative costs as well.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".