Exchange Rate Puzzles: Evidence from Rigidly Fixed Nominal Exchange Rate Systems
Bibliographic record
Abstract
We examine several major exchange rate puzzles: the excess volatility of real exchange rates; their excess reaction to the real interest rate differentials; the uncovered interest rate parity (UIP) puzzle; the excess persistence of real exchange rates; the exchange rate disconnect puzzle; and the consumption correlation puzzle. We examine the behaviour of real exchange rates among pairs of economies that have rigidly fixed nominal exchange rates, eg countries within the euro area, regions in China and Canada, and Hong Kong SAR vis-à-vis the United States, compared with that among non-euro-area OECD economies. Our results suggest that some of these puzzles are less puzzling under a rigidly fixed exchange rate regime. In particular, real exchange rates appear to have no or little excess volatility; excess reaction of the real exchange rate to real interest rates is less common; there is less disconnect between the real exchange rate and the economic fundamentals; and uncovered interest rate parity appears to hold more frequently in these economies. However, real exchange rates are as persistent in these economies as in the floating rate economies and there appears to be little difference in risk-sharing across countries with fixed versus floating nominal exchange rates. These results may have implications for exchange rate modelling.
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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 | 0.006 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".