International capital markets during the COVID-19 crisis
Bibliographic record
Abstract
This article analyses the main trends in securities issuance activity on international markets in 2020, a year in which capital markets were very buoyant despite the COVID-19 crisis. In 2020, record figures were posted for issues on fixed-income markets globally, driven by the measures adopted by governments and central banks to smooth financing and foment market liquidity. In terms of sectors, issuance by the public sector and non-financial corporations increased, while there were declines in the banking sector. By region, increases in issuance volumes were across the board, with notably greater dynamism in the United States and the United Kingdom. Finally, as regards time horizon, there was a strong increase in the second quarter of the year, with record figures posted. This may have been due to the fact that many issuers attempted to bring forward their issues in that quarter given the enormous uncertainty over the course of the pandemic and future financing conditions. Equity market issues were also notably buoyant, with figures not recorded since 2009.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".