Foreign Portfolio Investment Response to Monetary Policy Decisions in Nigeria: A Toda-Yamamoto Approach
Bibliographic record
Abstract
This paper examined the response of foreign portfolio investment to Monetary Policy decisions of the Central Bank of Nigeria using monthly data spanning January 2007 to December 2018. The study adopted the Toda-Yamamoto Causality model and Generalized Impulse Response Function for analysis. The results showed that changes in monetary policy stance could only impact the behavior of foreign portfolio investment with 6-month lag and with marginal impact. This implies that monetary policy could still be effective even if the CBN decides to lose policy stance without losing significant capital flight. The conclusion from the findings is that monetary policy is just a signaling instrument for portfolio investors in Nigeria because it influences foreign portfolio investment through the Treasury bill rate rather than through MPR and CRR. The marginal response of investment due to changes in policy rate from the GIRF validate the TY results by indicating that monetary policy rate changes on its own may not be what investors are concern about, rather the expectation of the rates future path. The cash reserve ratio as a monetary policy tool does not seem to exert any impact on foreign portfolio investment.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".