The Global Financial Crisis and Its Impact on Trade: The World and the European Emerging Economies
Bibliographic record
Abstract
This paper describes how the global financial crisis of 2007-2010 impacted trade both globally and more specifically for the European emerging economies, which in terms of GDP decline, were the most negatively impacted economies in the world. Just as with GDP, the trade of the European emerging economies was more severely impacted by the crisis than the trade for other regions of the world; exports for over one half of these economies declined by more than 50 per cent between the third quarter of 2008 and the first quarter of 2009. Despite these large declines, the geographical and sectoral distribution of their trade remained relatively stable. Most of these economies adjusted to the shock with a currency depreciation of about 20 per cent. The current account deficits of many of these economies which were quite large prior to the crisis were reduced significantly. Although there were some increases in protectionist measures and they did have a beggar-thy-neighbor component, in many cases these measures reflected macroeconomic policy failures, especially regarding the coordination of fiscal stimulus programs, and may have been welfare improving second best policies. The crisis is unlikely to result in major design changes in the world trading system, although the opposite is true for the world financial system.
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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 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".