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Record W3125587486 · doi:10.1093/cesifo/ifw013

Indirect Tax Initiatives and Global Rebalancing

2016· article· en· W3125587486 on OpenAlexaff
Chunding Li, John Whalley

Bibliographic record

VenueCESifo Economic Studies · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsCentre for International Governance InnovationWestern University
Fundersnot available
KeywordsEconomicsEndogeneityInternational economicsWelfareGlobal imbalancesTax revenueGeneral equilibrium theoryRevenuePublic economicsMacroeconomicsCurrent accountFinanceEconometricsMarket economyExchange rate

Abstract

fetched live from OpenAlex

This paper discusses how joint cross country indirect tax initiatives can be used to achieve global rebalancing. We suggest that if China and Germany (as major surplus countries) switch their present VAT systems from a destination principle to an origin principle, and the US (as the major deficit country) adopts a VAT on a destination principle VAT, jointly these actions can significantly reduce the three countries’ joint imbalances and so contribute to global rebalancing. We use a numerical general equilibrium model with a monetary structure incorporating inside money to capture endogeneity of trade imbalances, and to also investigate the potential impacts of such initiatives. These confirm that VAT structures are not only good for global rebalancing but also the changes we consider are beneficial for welfare and revenue collection. Our research is aimed to inject new ideas to the present global rebalancing debate. (JEL codes: F17; H21; C68)

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.036
GPT teacher head0.255
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes1
Has abstractyes

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