The international equity holdings of euro area investors
Bibliographic record
Abstract
Introduction The integration of euro area financial markets since the launch of the euro in 1999 has been at the centre of attention in policy debate and academic literature. This chapter complements this much-explored line of research by examining a subject that has attracted much less attention – namely, the characteristics of the euro area's external portfolio investment, and particularly the geographical allocation of the international equity portfolios held by euro area investors. The geography of the euro area's external equity holdings is important for several reasons. First, the level of holdings in each international market is a direct determinant of the euro area's exposure to external financial shocks. Second, it is also useful to assess whether international investment provides diversification against internal risks. Third, differences in the composition of international portfolios between the euro area and other major economic blocs (e.g. the United States and Japan) may generate asymmetric responses to international financial crises or global shocks, which in turn may pose a challenge for coordinated management of the international financial system. Our empirical work is made possible by the release of the International Monetary Fund's Coordinated Portfolio Investment Survey (CPIS). This dataset, described more in detail in section 5.2, provides a unique perspective on the geographical patterns of international portfolio holdings for most major international investors, including the entire euro area.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".