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Record W3021201660

International Private Transfers and Optimal Tax Structure in Developing Economies

2016· article· en· W3021201660 on OpenAlexvenueno aff
Ikuho Kochi, Ra ̈ l Alberto Ponce Rodr ̈aguez

Bibliographic record

VenueReview of Economics and Finance · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsCommodityState income taxIndirect taxConsumption (sociology)Value-added taxAd valorem taxTax reformMonetary economicsMicroeconomicsLabour economicsMacroeconomicsPublic economicsMarket economy
DOInot available

Abstract

fetched live from OpenAlex

In this paper we examine the optimal tax structure for a developing economy with international inter-family transfers. Our analysis characterizes conditions to identify the main determinants of the design of both the commodity and income tax. We find that these determinants change depending on the signs and values of the direct and cross price elasticities. A benchmark result of the literature suggests that the aggregate level of consumption, the weighted tax burdens from consumption and the efficiency costs of commodity taxes are the main determinants of a commodity tax. Our analysis suggests additional determinants, such as the aggregate level of income, the socially weighted aggregate level of labor income and the weighted aggregate elasticity of the supply of labor and income. A similar conclusion is obtained for the determinants of the income tax. Our analysis also provides a rationale to limit the use of the commodity tax and to increase the size of the income tax on the tax structure of this economy.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.217
Teacher spread0.195 · 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 designTheoretical or conceptual
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

Citations1
Published2016
Admission routes1
Has abstractyes

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