A Panel Data Analysis of the Validity of Uncovered Interest Rate Parity (UIRP) in Selected African Countries
Bibliographic record
Abstract
The theory of interest rate parity (covered and uncovered) has been severally examined by scholars from different backgrounds. Results from empirical studies have been mixed. Macroeconomics of Nation States are not monolithic. These variations in macroeconomic behaviour conditions exchange rate movements and thus interest rate changes. Even temporal macroeconomic policies such as the Certificate of Capital Importation (CCI) in Nigeria and similar policy in Malaysia could distorts the application of the theory of interest rate parity across board. Given that such distortions are rift, it is difficult to obtain a perfect result for IRP (Covered or Uncovered). This paper examined uncovered interest rate parity using the methodology of applied financial econometrics of panel data in selected African countries. The result is wholesomely inconclusive. While parity is applicable between Nigeria, Kenya and Egypt, it is not the case with Botswana and Ghana.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".