Capital Flows to Latin America and the Caribbean: Third Quarter 2019
Bibliographic record
Abstract
These are the main highlights of the Capital Flows to Latin America, Third Quarter 2019 edition: • International bond issuance from Latin America and the Caribbean (LAC) in the third quarter (Q3) of 2019 was US$ 39.3 billion. It was up 17% from the second quarter, and up 541% from the third quarter of 2018, and it was the highest third-quarter issuance since 2010. • From January to October 2019, the region’s total bond issuance reached US$ 103 billion, 20% higher than in the same period in 2018. • The three top issuers, sovereign and corporate issuance combined, accounted for 65% of the total issuance in the first ten months of 2019 – they included Mexico (30%), Brazil (23%) and Chile (12%). Corporate issuance represented 67.5% of the total. • From January to October 2019, both Latin American stocks and debt spreads partially recovered from the rout caused by the increase in volatility and risk perception in global markets in the second half of 2018. The JPMorgan EMBIG Latin component tightened 144 basis points, while Latin American stocks gained 8.2% according to the MSCI Latin American index. • On balance, credit quality has deteriorated this year. There were six credit rating upgrades and seven downgrades from January to October of 2019. In November, there was one more downgrade. When looking at all credit rating actions, including outlook revisions, there were eleven positive and eighteen negative actions year-to-date (as of November 22). • Finally, there was a recovery in green bond issuances from the region. From January to October 2019, green bond issuances in international markets amounted to US$ 4.6 billion, which represented 4.5% of the region’s total international bond issuance. • In June, Chile became the first sovereign in the region to issue green bonds
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".