Determinants of Economic Growth: Evidence from Somalia
Bibliographic record
Abstract
Somalia has suffered enormous instability and civil war in the last three decades, which have impacted the population as well as the economy of the country. Although Somalia is the one of the most impoverished and corrupt nations in the world, it has registered small growth in recent years. The people of Somalia are entrepreneurial by nature and have established business firms both outside and inside the country. This paper aims to investigate empirically the causal relationships between economic growth and variables such as exports (X), foreign aid (FA), government expenditure (GE), gross capital formation (GCF), and foreign direct investment (FDI). The unit root of the data was tested for all variables, and the variables were non-stationary in the level model but stationary in the first-difference model. The null hypothesis of no co-integration was rejected, and the tests revealed a causal relationship among the variables in the study. Four of the six explanatory variables were not statistically significant. Only the variables of GCF and FDI were statistically significant for economic growth.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".