Currency Misalignments and Optimal Monetary Policy:
Bibliographic record
Abstract
Exchange rates among large economies have fluctuated dramatically over the past 30 years. The dollar/euro exchange rate has experienced swings of greater than 60 percent. Even the Canadian dollar/US dollar exchange rate has risen and fallen by more than 35 percent in the past decade, but inflation rates in these countries have differed by only a percentage point or two per year. Should these exchange rate movements be a concern for policymakers? Or would it not be better for policymakers to focus on output and inflation and let a freely floating exchange rate settle at a market determined level? Empirical evidence points to the possibility of “local-currency pricing ” (LCP) or “pricing to market. ” 1 Exporting firms may price discriminate among markets, and/ or set prices in the buyers ’ currencies. A currency could be overvalued if consumer prices are generally higher at home than abroad when compared in a common currency, or undervalued if these prices are lower at home. 2 Currency misalignments can be very large even in advanced economies. In a simple, familiar framework, this paper draws out the implications for monetary
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".