Domestic Financial Architecture and Demand Side Intermediation Performance: Finametric Intertemporal Evidence From Nigeria
Bibliographic record
Abstract
This study aimed at unveiling the effects of the bank-based domestic architectural prescription on the demand side intermediation performance of banks in Nigeria. Finametric intertemporal long- and short-run modelling and estimations were made using the Johansen and Jusellius approach to cointegration, error-correction parameter estimation, and the VAR-Granger-causality/block-exogeneity-Wald tests. These were applied against quarterly data from 2010Q1 to 2022Q4. Results reveal that the architectural variables of MPR, SLR, and CRR jointly caused variations in the RCG demand side financial intermediation Performance of banks, both in the long- and short-runs. Individually, MPR negatively but strongly cause significant changes in the RCG performance, in both runs. SLR strongly and positively cause variations in RCG, in both runs. The CRR negatively, but does not affect RCG, in both runs. Policy options would include the systematic and carefully-timed reduction of the MPR (thereby, encouraging banks’ access to the discount window). Secondly, systematic and well-timed increase in the SLR would be a concerted policy alternative to the monetary authorities.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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".