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Record W4403165189 · doi:10.1111/saje.12387

US suspension policy from the African Growth and Opportunity Act (AGOA): An estimation of the missing exports from sub‐Saharan Africa

2024· article· en· W4403165189 on OpenAlex
Zakaria Sorgho

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSouth African Journal of Economics · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEstimationEconomicsDevelopment economicsInternational trade

Abstract

fetched live from OpenAlex

Abstract The African Growth and Opportunity Act (AGOA) is a unilateral duty‐free access program granted by the United States (US) to exports from sub‐Saharan African (SSA) countries. However, provisions of the AGOA text specify that countries can be suspended from the program in case of political turmoil and human rights violations that threaten democracy and the rule of law. This paper constructs a two‐step framework combining matching techniques and gravity regression to quantify the loss of exports due to AGOA suspensions using high‐disaggregated data of exports (10‐digit HTS level) from Africa to the US during 2001–2020. The AGOA suspension resulted in a 54% decline in SSA countries' exports to the US. Estimations suggest that, since 2004, the US suspension policy led to a reduction in exports from suspended countries of approximately 691 million USD on average per year. Over the 17 years (2004–2020), the suspended countries lost a total of 11.7 billion USD in the value of their exports to the US.

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.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.068
GPT teacher head0.223
Teacher spread0.155 · 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