The Ability of Selected European Countries to Face the Impending Economic Crisis Caused by COVID-19 in the Context of the Global Economic Crisis of 2008
Bibliographic record
Abstract
This paper is devoted to the ability of selected European countries to face the potential economic crisis caused by COVID-19. Just as other pandemics in the past (e.g., SARS, Spanish influenza, etc.) have had negative economic effects on countries, the current COVID-19 pandemic is causing the beginning of another economic crisis where countries need to take measures to mitigate the economic effects. In our analysis, we focus on the impact of selected indicators on the GDP of European countries using a linear panel regression to identify significant indicators to set appropriate policies to eliminate potential negative consequences on economic growth due to the current recession. The European countries are divided into four groups according to the measures they took in the fiscal consolidation of the last economic crisis of 2008. In the analysis, we observed how the economic crisis influences GDP, country indebtedness, deficit, tax collection, interest rates, and the consumer confidence index. Our findings include that corporate income tax recorded the biggest decline among other tax collections. The interest rate grew in the group of countries most at risk from the economic crisis, while the interest rate fell in the group of countries that seemed to be safe for investors. The consumer confidence index can be considered interesting, as it fell sharply in the group of countries affected only minimally by the crisis (Switzerland, Finland).
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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 | 0.003 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 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".