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Record W2184883209

Textile and Apparel Barriers and Rules of Origin in a Post-ATC World

2007· article· en· W2184883209 on OpenAlexaboutno aff
Alan Fox, William Powers, Ashley Winston

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsClothingTextileWelfareTariffQuarter (Canadian coin)Rules of originEconomicsLiberalizationBusinessInternational economicsInternational tradeCommerceMarket economy
DOInot available

Abstract

fetched live from OpenAlex

Although textile and apparel imports from most countries entered the United States quota free after the expiration of the Agreement on Textiles and Clothing on January 1, 2005, substantial quantitative restraints remained for Chinese and Vietnamese imports. These countries were respectively the first and eighth largest exporters of textiles and apparel to the United States, so these quantitative restraints remain important barriers to U.S. imports. This paper uses the USAGE– ITC model to estimate U.S. welfare gains and sectoral impacts of removing the remaining restraints on textiles and apparel imports. This analysis includes a new and detailed examination of textile and apparel preferential rules of origin. The shocks applied in the simulation include large declines in foreign demand for U.S. textile inputs in sectors in which U.S. exports are currently driven by rules of origin, and export price reductions that would accompany the elimination of rule-of-origin compliance costs in these sectors. Liberalization of textile and apparel barriers and rules of origin is estimated to increase U.S. welfare by $3.4 billion (net) while decreasing U.S. textile and apparel output by $11.0 billion. Eliminating only quantitative restraints provides over half of the welfare gain but causes less than 2 percent of the output loss, with a large decline only in the sock sector. Tariff elimination provides about one quarter of the welfare gain at a cost of 13.3 percent of the output loss, while elimination of rules of origin accounts for the remaining 23.3 percent of increased welfare and 84.9 percent of the overall output reduction.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.213
Teacher spread0.169 · 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.

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

Citations7
Published2007
Admission routes1
Has abstractyes

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