Effect of COVID-19 on International Trade among the Visegrad Countries
Bibliographic record
Abstract
The impact of the COVID-19 pandemic has been detrimental to all countries, despite the continuous efforts of governments on all continents to attempt to mitigate its damaging effects. All economic and social indicators have worsened. This study explores the impact of COVID-19 on international trade among the Visegrad Four (V4) countries. We employ data from Eurostat and FRED to explore this influence, using the monthly import and export data for the 2010 M1–2021 M4period. We estimate the trade model for each member country of the V4, exploring their trade relations with other V4 members. We employ a shift dummy and impulse dummy to show the effect of country lockdowns initiating possible structural change. After exploration, we found that the COVID-19 impact was evident in all countries, but not with the same strength. Looking outside the V4 group, we can also see that there are strong trade relations with Germany, which is the strongest European economy. For further exploration, we suggest investigating these outside links to complete the picture.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".