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Record W2211854089

Tax Obstacles for the Development of an Effective Euro-Mediterranean Free-Trade Area. An IFTA model for the European Union?

2014· preprint· en· W2211854089 on OpenAlexaboutno aff
José Miguel Martín Rodríguez

Bibliographic record

VenueRePEc: Research Papers in Economics · 2014
Typepreprint
Languageen
FieldSocial Sciences
TopicEU Law and Policy Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsExciseEuropean unionHarmonizationInternational tradeHaulageTax harmonizationFree tradeInternational economicsBusinessInternational free trade agreementEconomicsIndirect taxTax competitionTax reformPublic economicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

As we know, the European Union has faced the challenge of harmonization in the tax field with varied results. We may think that the advanced harmonization in indirect taxes (custom duties, VAT and excise duties) has reduced the distortions that they may create in the intra-EU commerce. Far from this assumption, in the paper we will underline how the lack of a complete harmonization may create competitive advantages in certain countries and sectors. Specifically, we will examine how the road haulage sector is affected by the differences in diesel excise duties among Member States. The proposal for a Euro-Mediterranean Free-Trade Area would face the same problems as the European Union. If there are distortions inside the European Union, the extension of the free trade area to other mediterranean countries would possibly worsen it. This is why we suggest the establishment of a system equivalent to the IFTA (International Fuel Tax Agreement), existing in the United States and Canada, in order to achieve an efficient haulage system free of tax distortions.

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)0.018
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.377
Teacher spread0.295 · 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 designSimulation or modeling
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
Published2014
Admission routes1
Has abstractyes

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