Pitfalls on the Road to Fiscal Decentralization Vito Tanzi Economic Reform Project
Bibliographic record
Abstract
this paper is to discuss a range of issues related to fiscal decentralization, focusing in particular on possible alternatives to decentralization and various pitfalls that may be associated with it. Unlike much of the previous literature on the subject, therefore, this paper will pay less attention to the actual processes of decentralization and more on whether decentralization is the right direction for a country to choose. I. THE TREND TOWARD FISCAL DECENTRALIZATION The term "fiscal decentralization" refers to an increase in taxing and/or spending responsibilities given to subnational jurisdictions. In many cases of fiscal decentralization, additional layers such as states, provinces, and regions are created. A related term, "fiscal federalism," is an advanced form of fiscal decentralization. Until recent years, countries seemed to be divided into two relatively distinct groups: the "federal" and the "unitary." In federal countries such as Argentina, Australia, Brazil, Canada, Germany, India, Nigeria, Russia, and the United States, subnational governments have important and independent responsibilities for public spending and taxation. These responsibilities are often outlined in each country's constitution, which explicitly recognizes the existence and the powers of the subnational jurisdictions. In unitary countries such as France, Japan, and Chile, on the other hand, spending and taxing decisions are made mostly at the level of the national government, although some spending may be carried out by decentralized agencies or institutions acting on its behalf
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".