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Record W1541760063

Alternative fiscal visibility estimates for some OECD countries with three levels of territorial government levels

2002· preprint· en· W1541760063 on OpenAlexaboutno aff
Miguel Roig-Alonso

Bibliographic record

VenueEconstor (Econstor) · 2002
Typepreprint
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsnot available
Fundersnot available
KeywordsVisibilityRevenueMultiplicative functionGovernment (linguistics)EconomicsPublic economicsValue (mathematics)EconometricsLocal governmentRest (music)Government revenueGeographyMathematicsStatisticsAccounting
DOInot available

Abstract

fetched live from OpenAlex

The size and pattern of any public budget depend, among other factors, on the visibility of both the burdens and benefits of public revenue and expenditure. Furthermore, such visibility is a necessary - not a sufficient - condition for an efficient allocation of resources between the private and public sector of an economy. Although the importance of this visibility has been well known by academicians and practitioners for a long time, attempts to quantify it by taking the internal structure of every type of revenue or expenditure and its relative financial weight in a fiscal system into consideration are recent, and indicators used till now rest on several structural parameters, each of them conventionally ranging from 0 to 1, which are combined in a multiplicative way. For this reason, a 0 estimate will always result as one of such factors is, at least, also 0. Starting from the same parameters, factors, and initial values, an alternative and probably more fruitful way to measure visibility of burdens and benefits of a public budget can consist of combining them in an additive instead of multiplicative way. Then a null parametric value will not result in a 0 estimate, and calculations can show higher final values which could be much more sensitive to the initial values of other parameters and factors. The aim of this contribution, based on a recent research, is to present and compare new additive indicators applied to local, intermediate, and central territorial government levels in Austria, Canada, Germany, Spain, Switzerland, and USA by using data and qualitative information provided by the International Monetary Fund. Comparisons, conclusions, and comments are offered for general criticism, discussion, and development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.034
GPT teacher head0.289
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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