Exchange Rate Overshooting: A Reassessment in a Monetary Framework
Bibliographic record
Abstract
Most empirical studies on monetary policies have found exchange rate effects that are inconsistent with Dornbusch's overshooting hypothesis. Bjornland (2009) finds evidence of exchange rate overshooting by using interest rate alone as the monetary policy instrument. However, theoretically consistent way of identifying monetary policy requires capturing dual interaction between central bank's reaction to economic conditions and private sector's response to policy action. This calls for the introduction of "monetary‟ aggregates back in the models of exchange rate determination. Motivated by Bjornland's result, identification is achieved by imposing short-run and long-run restrictions while keeping the short-run interactions between monetary policy and exchange rate free. Using more appropriate econometric technique in a model aligned to \ntheory, our paper rediscovers the validity of Dornbusch Overshooting hypothesis for Australia, Canada, New Zealand and Sweden more accurately and more robustly than Bjornland's original model.
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.008 | 0.018 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.010 |
| 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".