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Record W6982365242

The Impact of United States Anti-dumping duties on 3rd Country U.S. Trading Partners

2020· other· en· W6982365242 on OpenAlexaboutno aff

Bibliographic record

VenueCU Scholar (University of Colorado Boulder) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsChinaDutyPanel dataTrade barrierWorld tradeTrade diversionTrade war
DOInot available

Abstract

fetched live from OpenAlex

Anti-dumping duties are a form of discriminatory trade barrier that can divert trade from an intended destination country to some other 3rd country.This paper examines the effect of these duties imposed by the United States on Chinese products on increases in the exports of those products from China to other United States trading partners.Utilizing Chinese export panel data and selecting the European Union, Canada, and Japan as 3rd country trading partners, I estimate that, over time before and after an anti-dumping duty is imposed, 6-digit level harmonized system exports from China into these 3rd countries that face some anti-dumping duties imposed by the United States on China at the 8-digit level are predicted to increase 156 percentage points more than similar, and unaffected, 6-digit products.These findings indicate that U.S. anti-dumping duties imposed on China impact and possibly damage other major U.S. trade partners through the process of export trade diversion.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.026
GPT teacher head0.280
Teacher spread0.254 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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