Exportações de cacau da Nigéria: uma abordagem do modelo gravitacional
Bibliographic record
Abstract
portuguesQuais sao os principais fatores que afetam os fluxos de exportacao de cacau da Nigeria? Ao responder a esta pergunta, os autores sugerem um modelo de gravidade especifica de mercadoria com tres abordagens analiticas diferentes (o Modelo de Selecao de Amostras de Heckman, o Minimo Quadrado Generalizado e a Pseudo Maxima Verossimilhanca de Poisson), com base em um periodo de 24 anos de dados em painel para a Nigeria e seus parceiros importadores para estimar os modelos. Os resultados mostram que o PIB, a politica cambial, a OMC, a UE e a ligacao colonial estao positivamente associados aos fluxos de exportacao de cacau da Nigeria. Alem disso, e observado o impacto negativo do PIB per capita, sem litoral, distância, UA e CEDEAO. Destaca-se a necessidade de ampliacao das exportacoes para os parceiros comerciais, especialmente os membros da UE (Holanda, Alemanha, Franca, Reino Unido, Belgica, Espanha, etc.), Canada, Malasia e Estados Unidos. Esses resultados sao importantes para a formulacao de uma politica comercial futura que possa impulsionar as exportacoes de cacau nigeriano. Isso acabaria por contribuir para a diversificacao das exportacoes nigerianas e tambem aumentar as receitas externas do pais. EnglishWhat are the major factors affecting Nigeria’s cocoa export flows? In answering this question, the authors suggest a commodity- specific gravity model with three different analytical approaches, (the Heckman Sample Selection Model, the Generalised Least Square, and the Poisson Pseudo Maximum Likelihood), based on a period of 24 years of panel data for Nigeria and it’s 36 importing partners to estimate the models. The results showed that GDP, exchange rate policy, WTO, EU, and colonial link are positively associated with the Nigerian cocoa export flows. Further, the negative impact of the GDP per capita, landlocked, distance, AU, and ECOWAS are observed. The need for the expansion of exports to the trading partners, especially the EU members (Netherlands, Germany, France, United Kingdom, Belgium, Spain, etc.), Canada, Malaysia, and the USA is particularly highlighted. These results are important for the formulation of future trade policy that could boost up the Nigerian cocoa exports. This would eventually contribute to the diversification of the Nigerian exports and also enhance the country’s foreign earnings
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".