Wealth Transfer Taxation: An Empirical Investigation
Bibliographic record
Abstract
We present an empirical model of wealth transfer taxation in the revenue systems of the G7 countries - Canada, France, Germany, Italy, Japan, the U. K. and the U. S. - over the period from 1965 to 2009. Our model emphasizes the influences of population aging and of the stock of household wealth in an explanation of the past and likely future of this tax source. Simulations with the model using U.N.demographic projections and projections of household wealth suggest that even in France and Germany where reliance on wealth transfer taxation has been increasing for part of the period studied, wealth transfer taxes can be expected to wither away as population aging deepens over the next three decades. Our results indicate that recent tax designs that rely upon the taxation of wealth transfers to preserve equity in the face of declining taxation of capital incomes may be, in this respect, politically infeasible for the foreseeable future. We conclude by using the case of wealth transfer taxation to raise the general question of the extent to which the consistency of a proposed reform with expected political equilibria ought to play a role in the design of a normative policy blueprint.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".