Examining International Parity Relations between Kenya and Uganda: A Cointegrated Vector Autoregressive Approach
Bibliographic record
Abstract
This paper analyses empirically the purchasing power parity, the uncovered interest parity and the real interest parity (Fisher parity) between Kenya and Uganda. The paper first tests the three parity relations using stationarity tests. Afterwards the study jointly models international parity conditions, namely PPP, RIP and UIP using a Cointegrated Vector Autoregressive approach. From the analysis of the individual parities, there is no evidence that the individual parities hold between the two countries except for RIP. On the other hand the joint VAR model establishes that the Kenya-Uganda inflation rates, interest rates, and the real exchange rate have followed a long-run equilibrium-correcting behavior. The joint Cointegrated VAR analysis reveals that all the endogenous variables explain more than 99.95% of the VAR model. This indicates a fast correction towards the long run equilibrium of the parity relations. Hence when the three parity relations are jointly modeled, it can be argued that Uganda has shown a tendency to converge to Kenya both in both nominal and real terms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".