Central bank reserve management : new trends, from liquidity to return
Bibliographic record
Abstract
Contents: Preface 1. Central Bank Reserve Management: Trends and Issues Age F.P. Bakker and Ingmar R.Y. van Herpt PART I: THE SIZE OF CENTRAL BANK RESERVES 2. Assessing the Benefits and Costs of Official Foreign Exchange Reserves Robert McCauley 3. The Politics and Micro-Economics of Global Imbalances Avinash Persaud 4. The Cost-Benefit Approach to Reserve Adequacy: The Case of Chile Esteban Jadresic 5. Foreign Reserve Adequacy from the Asian Perspective Hidehiko Sogano 6. Dealing with Reserve Accumulation: The Case of Korea Heung Sik Choo 7. Reserve Accumulation: A View from the United States Matthew Higgins PART II: RESERVE MANAGEMENT: RETURN VERSUS LIQUIDITY 8. Trends in Reserve Management by Central Banks Jennifer Johnson-Calari, Robert Grava and Adam Kobor 9. Implications of Growing Reserves of Central Banks for Asset Allocation Amy Yip 10. A Developing Country Case Study - Setting the Strategic Benchmark Duration and Currency Allocation Vinod Kumar Sharma 11. Observations on the Return versus Liquidity Debate: The Canadian Perspective Donna Howard 12. A European View on Return versus Liquidity Pentti Hakkarainen and Mika Poso 13. The Composition of Central Bank Reserves: The Market Perspective Joachim Fels 14. Central Bank Risk Management: The Case of the Czech National Bank Ludek Niedermayer 15. Returns from Alpha and Beta: An Equilibrium Approach to Investing Bob Litterman 16. The Conservative Approach to Central Bank Reserve Management Hans-Helmut Kotz and Isabel Strauss-Kahn PART III: IMPLICATIONS FOR CENTRAL BANK BALANCE SHEETS 17. Central Bank Balance Sheets: Comparisons, Trends and Some Thoughts Francesco Papadia and Flemming Wurtz 18. Governance Aspects of Central Bank Reserve Management Age Bakker 19. Too Much of a Good Thing: Reserve Accumulation and Volatility in Central Bank Balance Sheets Herve Ferhani
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".