Appraisal of The Effect of The Global Financial Meltdown on The Nigerian Money Market
Bibliographic record
Abstract
This study looked at the effect of the global financial meltdown on the Nigerian money market. To start with, it identified the major problems associated with the Global financial crisis and its effects on the Nigeria economy. As the crisis affect trade and investment flows, the Nigerian money market have so far triggered a rebound and allayed panic about the systemic financial collapse. The Ordinary Least Square (OLS) technique of regression analysis was adopted in analyzing the empirical data for Non-crisis period from 2000-2005 and the crisis period from 2006-2009 after necessary adjustment were carried out on the relevant data. Money supply/Gross Domestic Product (which stands as proxy for the impact of the Global financial meltdown) serves as the dependent variable while other money market indicators (TBs, CPs, Bas, CDs, BLR and INF) serve as the explanatory variables in the first and second models. The findings from the empirical analysis showed that in the non-crisis era (2000-2005) the explanatory variables all met apriori expectation. However, in the crisis era, only the coefficient of inflation retained its apriori sign. This implies that economic activities were adversely affected by the global financial meltdown as seen in the adverse effect on financial deepening. This in turn has a corresponding effect on the Nigerian money market, thus dis-stabilizing its indicators. This can be attributed to the failure of the Nigerian money market regulator to fulfill its primary responsibilities of supplying needed funds to critical sectors where such funds are needed during the period of financial crisis. This study therefore recommends that adequate procedures for handling systemic crisis should be drawn up promptly in preparation for contingencies. Monetary authorities should identify the vulnerabilities of the money market and safeguard its effectiveness as a means of reducing the further effects of the financial meltdown on Nigerian economy at large.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".