The Impact of the Covid-19 Pandemic on Reserve Adequacy: Evidence From Middle Income Countries
Bibliographic record
Abstract
In order to examine the impact of the COVID-19 pandemic on reserve adequacy levels in 70 middle income EMC’s we employ the IMF’S risk weighted metric, along with three other standard measures. Our research suggests that over 50% of these countries were ill-prepared to handle the financial risks posed by COVID- 19 beyond 2020. We find that the demand for international reserves during the study period emphasized financial stability, rather than trade related vulnerabilities. We observed that reserve demand is influenced by the need to meet a more broad-based adequacy level, with less emphasis on individual sectorial vulnerabilities. Additionally, the financial stability variables, such as the dummy variable for the fixed exchange rate, broad money/reserves, and short-term debt/ reserves, carry a greater proportion of the weights than the trade related variables, namely, (export + import)/GDP, export/GDP, and import/GDP. This finding lends support to the notion that the motivations for holding reserves by EMCs may be shifting away from trade related vulnerabilities and moving towards mitigating susceptibilities in the financial sector.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".