Foreign exchange intervention as a monetary policy instrument : evidence for inflation targeting countries
Bibliographic record
Abstract
1 Introduction.- 1.1 Background.- 1.2 Approach to the Problem and Research Strategy.- 1.3 Structure of the Analysis.- 2 The Conventional View on Inflation Targeting.- 2.1 Definition and Elements of Inflation Targeting.- 2.1.1 Lack of an Explicit Intermediate Target.- 2.1.2 Price Stability as the Final Target.- 2.1.3 Publication of a Numerical Target.- 2.1.4 Transparent Communication of Central Bank Decisions.- 2.1.5 Increased Accountability of the Central Bank.- 2.1.6 Summary and Assessment.- 2.2 Adoption of Inflation Targeting.- 2.2.1 Overview.- 2.2.2 Country Selection.- 2.3 A Basic Model for (Closed-Economy) Inflation Targeting.- 2.4 Open Economy Inflation Targeting.- 2.4.1 Exchange Rate Pass-Through and Monetary Policy.- 2.4.2 The Svensson Model.- 2.4.3 The Ball Model.- 2.4.4 Two Critical Assumptions.- 3 Uncovered Interest Parity in Practice.- 3.1 The Rationale of Interest Parity.- 3.1.1 Covered Interest Parity.- 3.1.2 Uncovered Interest Parity.- 3.2 An Empirical Test for Inflation Targeting Countries.- 3.3 Consequences of the Failure of UIP.- 4 Sterilised Interventions as an Additional Policy Instrument.- 4.1 Explaining and Interpreting Sterilised Interventions.- 4.1.1 Channels for Influencing Exchange Rates.- 4.1.2 Sterilised Interventions as a Monetary Policy Instrument.- 4.1.3 Sterilisation Evidence for Inflation Targeting Countries.- 4.1.4 Managed Floating in Theory.- 4.1.5 Limitations of Sterilised Interventions.- 4.2 The Effectiveness of Sterilised Interventions: A Review of the Literature.- 4.2.1 The Intervention Debate.- 4.2.2 The Inefficiency of Sterilised Interventions in Monetary Models.- 4.2.3 The Portfolio Balance Channel of Interventions.- 4.2.4 Interventions as a Signal of Future Monetary Policy.- 4.2.5 Noise-Traders and the Role of Sterilised Interventions.- 4.2.6 The Microstructure Approach and Sterilised Interventions.- 4.2.7 Assessment of Intervention Models.- 5 Sterilised Foreign Exchange Intervention in Practice.- 5.1 Foreign Exchange Reserves as an Intervention Proxy.- 5.1.1 Reasons for Holding Foreign Exchange Reserves.- 5.1.2 Mechanics of Foreign Exchange Intervention.- 5.1.3 External Influences on Foreign Exchange Reserves and Their Adjustment.- 5.1.3.1 Identification and Correction of Valuation Effects.- 5.1.3.2 Estimation of Interest Earnings.- 5.1.4 The Correlation between Official Interventions and Reserves.- 5.1.5 Active versus Passive Interventions.- 5.2 Intervention Activity in Inflation Targeting Countries.- 5.2.1 Comparison of Intervention Capacities.- 5.2.2 Comparison of Reserve Changes.- 5.2.2.1 Correction for Valuation Changes.- 5.2.2.2 Correction for Interest Earnings.- 5.2.3 Identification of Intervention Activity.- 5.2.3.1 Absolute Reserve Changes.- 5.2.3.2 Normalisation with the Degree of Openness.- 5.2.3.3 Normalisation with the Size of Foreign Exchange Markets.- 5.2.3.4 Response to Shocks.- 5.2.4 Ranking of Intervention Activity.- 5.3 The Use of Interventions as an Additional Policy Instrument.- 5.3.1 Interventions and the Variation of Interest Rates.- 5.3.1.1 Interest Rate Volatility Compared.- 5.3.1.2 Frequency of Policy Rate Changes Compared.- 5.3.1.3 Interpretation of the Findings.- 5.3.2 Policy Reaction Functions and Exchange Rates.- 5.3.2.1 Evolution of Taylor Rules.- 5.3.2.2 Description of Data and Methods.- 5.3.2.3 Stationarity Tests.- 5.3.2.4 Country-Specific Results and Interpretation.- 5.4 Short Case Studies of the Country Experiences.- 5.4.1 New Zealand.- 5.4.2 Canada.- 5.4.3 Australia.- 5.4.4 United Kingdom.- 5.4.5 Sweden.- 6 Performance of Inflation Targeting: An Evaluation.- 7 Conclusion and Outlook.- List of Figures.- List of Tables.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".