Impact of Financial Intermediaries on Nigerian Economic Growth
Bibliographic record
Abstract
This paper empirically investigated the impact of financial intermediation of economic growth in Nigeria. Quarterly time series data generated from the World Bank Development indicator and the Nigerian Bureau of Statistic for the periods 1994Q1 to 2018q4 were used for the analysis, and Ordinary Least Squares (OLS) regression technique was adopted for the estimation of the hypotheses. Per-capita GDP was used as a measure of economic growth, while bank deposit, bank credit and bank reserves are measures of financial intermediation. Further investigation also show that bank deposit is positively and significantly related to GDPpc, suggesting that increase in bank deposit brings about 0.244193 increases in economic growth. We further observed that bank credit impacted positively on economic growth. Though, the impact was found to be insignificant. Hence, we also found bank reserve to assert significant and positive impacted on economic growth. From the findings, we suggest for good policy reforms that may promote the efficiency and the development of bank which serve as a critical factor for economic growth in Nigeria.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".