Revisiting the Monetary Sovereignty Rationale for CBDCs
Bibliographic record
Abstract
As currently articulated, the monetary sovereignty argument for central bank digital currencies (CBDCs) rests on the idea that without them, private and foreign digital monies could displace domestic currencies (a process called currency substitution), threatening the central bank’s monetary policy and lender-of-last-resort (LLR) capabilities. This rationale provides a crucial but incomplete picture of what is at stake in terms of monetary sovereignty. This paper seeks to expand and enhance this picture in three ways. The first is by looking at the consequences of currency substitution that go beyond the functions of a central bank—important considerations that have received less attention in public CBDC discussions. The second is by exploring key differences in monetary policy and LLR capabilities across currency-issuing countries or regions. More specifically, the paper highlights the variation in the degree of monetary sovereignty and the consequences that different countries face should they lose it. The third way is by assessing not only the implications but also the risks of currency substitution and showing how these are also likely to vary across countries. Contrasting the consequences and risks of substitution, the paper concludes by noting a potential inverse relationship between the impact and probability of losing monetary sovereignty.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 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".