Optimal exchange rate regimes: Turning Mundell-Fleming's dictum on its head
Bibliographic record
Abstract
A famous dictum in open economy macroeconomics --which obtains in the Mundell-Fleming world of sticky prices and perfect capital mobility --holds that the choice of the optimal exchange rate regime should depend on the type of shock hitting the economy.If shocks are predominantly real, a flexible exchange rate is optimal, whereas if shocks are mainly monetary, a fixed exchange rate is optimal.There is no obvious reason, however, why this paradigm should be the most appropriate one to think about this important issue.Arguably, asset market frictions may be as pervasive as goods market frictions (particularly in developing countries).In this light, we show that in a model with flexible prices and asset market frictions, the Mundell-Fleming dictum is turned on its head: flexible rates are optimal in the presence of monetary shocks, whereas fixed rates are optimal in response to real shocks.We thus conclude that the choice of an optimal exchange rate regime should depend not only on the type of shock (real versus monetary) but also on the type of friction (goods versus asset market).
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".