Exchange rate realignments and risks of deflation in North America
Bibliographic record
Abstract
The US dollar has strengthened in recent months against most major currencies, with the exception of the yen. It has also gained strength against emerging market currencies, and the US effective exchange rate has appreciated by just over 7 per cent in the past three months. Emerging market declines have been exacerbated in recent weeks by the turbulence on financial markets that has forced stock markets to interrupt trading on several occasions. Figure 13 shows effective exchange rates for the US, Canada, Mexico and Brazil. Central banks in Mexico and Brazil have intervened in currency markets in recent weeks to stem the decline of their currencies, which have dropped against the dollar by nearly 20 per cent in the case of Mexico and 40 per cent in Brazil since the beginning of September. If stock market trading stabilises, much of these losses should prove temporary. Our forecast assumes that a depreciation of 10 per cent in effective terms in the Brazilian real and 5 per cent in the Mexican peso is sustained. While this raises the inflationary outlook for these economies, gains in competitiveness will help moderate the impact of the global recession on Latin American economies. However, a more sustained depreciation will put the banking systems in these countries at risk as it becomes increasingly difficult to service debt in foreign currency.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".