Inflation Co-Movement Dynamics: A Cross-Country Investigation Using a Continuous Wavelet Approach
Bibliographic record
Abstract
The economic literature provides evidence that inflation rates can co-move across nations because of a host of reasons, ranging from low frequency changes in monetary policy to similar high frequency shocks. Hence, this paper investigates inflation rate co-movements between nine (9) African countries and their bilateral linkages with five (5) developed economies using continuous wavelets at different time scales or frequencies. Specifically, we examine the coherency and the phase relationship in time-frequency space in inflation rates of the selected countries. Several findings are documented. First, inflation rates co-movements in the nine African countries are time varying, multi-scale, and characterized by structural breaks. In addition, we find that inflation co-movements across countries in the Africa sub-region is weak at low frequencies. Furthermore, we find evidence of inflation co-movement between Africa and developed economies, suggesting that central banks and policy-makers in Africa need to monitor international price developments, and analyze their implications for their domestic economies. Second, we find that inflation rates in the selected African countries explain, on average, almost 80% of their own inflation variance over the whole sample period. Spillover analysis reveals that China and Canada account for a greater percentage of inflation variation in Africa.
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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".