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Record W3150915220

Trade Preference Erosion: Measurement and Policy Response

2009· preprint· en· W3150915220 on OpenAlexaboutno aff
Bernard Hoekman, Will Martín, Carlos A. Primo Braga

Bibliographic record

VenueRePEc: Research Papers in Economics · 2009
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsInternational economicsLiberalizationProtectionismEconomicsCommercial policyFree tradeInternational tradeEuropean unionPreferenceBeneficiaryMarket economy
DOInot available

Abstract

fetched live from OpenAlex

The multilateral trade system rests on the principle of nondiscrimination. The most-favored-nation (MFN) clause embodied in article one of the General Agreement on Tariffs and Trade (GATT) was the defining principle for a system that emerged in the post, Second World War era, largely in reaction to the folly of protectionism and managed trade that contributed to the global economic depression of the 1930s. From its origins, however, the GATT has allowed for exemptions from the MFN rule in the case of reciprocal preferential trade agreements. It also permits granting unilateral (nonreciprocal) preferences to developing countries. To provide some background for the debate on the potential extent and implications of preference erosion, the chapters in this volume review the value of preferences for beneficiary countries, assess the implications of preference erosion under different global liberalization scenarios, and discuss potential policy responses. One set of chapters focuses on the nonreciprocal preference schemes of individual industrial countries, particularly, Australia, Canada, Japan, the United States, and the member states of the European Union (EU). A second set of chapters considers sectoral features of these preference schemes, such as those applying to agricultural and nonagricultural products, and the important arrangements for textiles and clothing. A final set of chapters considers the overall effects of preferences and the options for dealing with preference erosion resulting from nondiscriminatory trade liberalization.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.188
GPT teacher head0.306
Teacher spread0.118 · 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 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

Citations32
Published2009
Admission routes1
Has abstractyes

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