Is Fiscal Federalism Different in the European Union?: a comparative analysis through the allocation function
Bibliographic record
Abstract
A political-economic model largely influenced by the monetarist school inspires European Economic and Monetary Union (EMU). Accordingly, neither income redistribution nor resource allocation is the cornerstone of economic policy mix. That role is reserved to the stabilisation function. Among those scholars who discuss whether the EU is comparable to existing cases of “conventional fiscal federalism”, the analysis is frequently concentrated on allocation and redistribution. Despite macroeconomic stabilisation is the key aspect of EMU, the paper undergoes a comparative analysis between the European Union (EU) and five mature federations (United States, Canada, Australia, Germany, and Switzerland) as far as resource allocation is concerned. It first surveys the operation of the allocation function in these countries, concluding that there are remarkable differences when the countries under examination are measured within a centralisation/decentralisation continuum. Resource allocation is subsequently reviewed in the context of EMU to capture convergences and divergences with the federations examined – and to what extent do convergent aspects contribute to put a label on the EU in terms of fiscal federalism. The awareness that the discussion is sometimes plagued with conceptual oversight – the confusion between the desirability and feasibility of fiscal federalism in the European integration context – paves the way to the empirical dimension. The paper concludes with an input from statistical data assessing to what extent inter-state solidarity exists (or is absent) in the EU.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".