Measuring Financial Fragmentation in the Euro Area Corporate Bond Market
Bibliographic record
Abstract
This paper analyses the determinants of euro area non-financial corporate bonds since the early 2000s, so as to gauge deviations from the law of one price. We decompose the spread between the yield of German, French, Italian and Spanish corporate bonds vis-à-vis the German Bund of similar maturity into country, credit and duration risk premia components via dummy regressions. We highlight three main findings. First, the initial phase of the financial crisis (2008–2009) caused an overall increase in credit risk premia. Since the beginning of 2013 credit risk premia are back to levels comparable to those preceding the financial crisis. Second, at the height of the euro area sovereign crisis (2011–2012), high credit risk premia were accompanied by strong and persistent signs of market fragmentation in Italy and Spain (but not in France). This fragmentation has reached its peak in the second half of 2012 and has started to recede only after the announcement of the OMT. Third, we provide a simple measure of financial integration across the big 4 member states of the 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 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".