The Effectiveness of Official Foreign Exchange Intervention in a Small Open Economy: The Case of the Canadian Dollar
Bibliographic record
Abstract
The Bank of Canada is one of very few central banks that has made records of the intraday timing of its intervention operations available to researchers. The authors investigate the effectiveness of sterilized intervention in the Canadian dollar exchange rate market over the period January 1995 to September 1998. They employ an event study methodology and different criteria for success, and use both daily data and high-frequency (intraday) intervention and exchange rate data. The time period covers two distinct intervention regimes, characterized by mechanistic and discretionary intervention, respectively. Furthermore, the authors address the issue of currency comovements by carrying out the analysis using both the readily observable Canadian dollar/U.S. dollar exchange rate and the Canadian dollar/U.S. dollar exchange rate adjusted for general currency co-movements against the U.S. dollar. When they analyze the high-frequency data, the authors find evidence that intervention systematically affects movements in the Canadian dollar/U.S. dollar exchange rate and in the desired direction, along with some evidence that intervention is associated with a reduction of exchange rate volatility. When investigating exchange rate movements around intervention events using daily data, the authors find some evidence supportive of effectiveness. These effects, however, are weakened when adjusting for currency comovements against the U.S. dollar.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".