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Record W3181823811 · doi:10.21203/rs.3.rs-610432/v1

Demand for Cashew Nut Exports of Guinea-Bissau (1990-2011): VAR Model Application

2021· preprint· en· W3181823811 on OpenAlexaff
Júlio Vicente Catéia

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsUniversité du QuébecUniversité Laval
Fundersnot available
KeywordsVariance decomposition of forecast errorsEconomicsExchange rateCashew nutVector autoregressionForeign exchangeCommodityDemand shockMonetary economicsAgricultural economicsEconometricsMarket economyAgricultural science

Abstract

fetched live from OpenAlex

Abstract This study aimed to estimate via VAR the reaction of the export demand for Guinea-Bissau Cashew nuts to the shocks of world income, exchange rate and of the foreign and domestic prices and of the effects of the Civil War, which occurred in the country from 1990 to 2011. The main results obtained by analyzing the impulse response function and variance decomposition, showed that changes in domestic price and exchange rates don’t explain the external demand for this commodity. External demand responds to changes in global income and foreign price. Moreover, the Civil War of 1998 influenced the foreign demand. In the long run, external demand for cashew nuts doesn’t react to shocks in any of the variables in the model.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.115
GPT teacher head0.364
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2021
Admission routes1
Has abstractyes

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