The Disaggregated Impact of Financial Development on the Effectiveness of Monetary Policy in Nigeria
Bibliographic record
Abstract
The fast development in the financial system has attracted researchers’ interest in studying its implication on the economy, though empirical evidence is highly limited on disaggregated levels. This study is undertaken to examine the impact of disaggregated financial development on the effectiveness of monetary policy in Nigeria. The study used Autoregressive Distributed Lag Model to capture the data-generating process as well as both short-run and long-run relationships. The scope of analysis ranged from 2000 quarter 1 to 2021 quarter 4 to circumvent the effect of regime changes, as the chosen time horizon represents the period of the uninterrupted civilian regime in Nigeria. The data are sourced from the Central Bank of Nigeria’s and the International Monetary Fund’s statistical databases. Moreso, quarterly frequency data are used to reflect the short-run nature of the monetary policy. The finding reveals financial market development enhances the effectiveness of monetary policy in terms of achieving both its primary and secondary objectives while financial institutions development does not. Given the findings, it is recommended that the Government together with the Central Bank of Nigeria should design policies that would enhance the efficiency of the financial market, particularly markets infrastructure and technology-based products to reduce information asymmetry and transactional costs to ease the way of doing business.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".