European Market Factors and Macroeconomic Fundamentals: Trend at Firm Level Including the IT Bubble and Sovereign Debt Crisis
Bibliographic record
Abstract
We analyse the trend in global, country and industry effects at firm level based on an extensive database of 2048 equities spread over 17 European economies and 10 industry groups, running from 1974 to 2013. We find significant increasing market integration and decreasing country effects for most countries and industries since the advent of the EMU. However, these effects are now reversing in the wake of the sovereign debt crises. Industrial factor effects have decreased in technological sectors and increased in “old economy” sectors since the bursting of the IT bubble, and are larger than country effects in most countries and industries. From a macroeconomic point of view, we report evidence of a link between the percentage of variance that can be attributed to the country effect and government budget deficits/surpluses and sovereign risks. More strikingly, we find that global common factor effects anticipate changes in GDP by one to three terms. These results support the notion of market integration having macroeconomic predictive power.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".