The impact of capital market on the economic growth of Nigeria
Bibliographic record
Abstract
The study assessed how the capital market affected Nigeria's economic expansion. Specifically, the impact of the Nigeria stock exchange's total value of transactions (TVTs), all-shares index (ASIs) and stock market capitalisation (MCAP) on Nigeria's economic development was evaluated. Time-series data covering 1986–2021 was obtained in the study. Estimation methods used in the study’s analysis include descriptive statistics correlation analysis, ARDL co-integration analysis, parsimonious error correction model, variance decomposition and other post-estimation tests. Discoveries from the study showed that MCAP positively impacts economic growth in the long and short run. The ASI affects economic growth positively and insignificantly in the long and short runs, and the TVTs exerts a significant positive effect on the economic growth of Nigeria. Hence, the study suggested that the Security and Exchange Commission should explore measures, including technological integration in trading activities, to deepen development in the capital market. Keywords: All-share index, gross fixed capital formation, market capitalisation, real gross domestic product, total value of transactions;
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".