Gravity model by panel data approach: empirical evidence from Nigeria
Bibliographic record
Abstract
Gravity trade model continues to be coveted for analysis of determinants of trade flows despite its lack of theoretical foundations. The main aim of the paper is to assess the determinants of the flow of Nigeria's exports using longitudinal data from 1999 to 2012. Extrapolating from the empirical literature, the paper constructs Nigeria's gravity trade model comprising nine EU countries, BRICS countries, Canada, Japan and the USA. Results from POOL and panel regressions - fixed and random effects show that market size and price index of destination countries positively drive trade flows in Nigeria, while relative factor endowment, economic similarities and geographical distance negatively affect Nigeria's trade flows. Furthermore, the paper found evidence in support of positive trade flows with the EU countries and negative trade flows with the BRICS countries and on account of cultural differences. Findings show that Nigeria's exports follow Linder hypothesis. These have important implications for economic, socio–cultural and bilateral trade negotiations for better trade performance in Nigeria in the future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".