Macroeconomic consequences of the COVID-19 pandemic
Bibliographic record
Abstract
The article puts forward the thesis that the COVID-19 recession has already passed, which makes it possible to make some other conclusions . It is emphasized that the recession was triggered mainly by temporary restrictions on social contacts and mobility that were “external” to the economy. For Russia, it was aggravated by discords among the OPEC+ members. It is established that the 2020 drop of economic activity turned out to be unprecedentedly deep and unprecedentedly short, in some cases even less than one quarter. Compared to other countries, Russia passed the crisis quite successfully, although the size of the Russian stimulus package was much smaller than in the most developed countries. It is noticed that around the world quite fast recovery began immediately after the mitigation of lockdowns. Relatively recent data allowed us to conclude that by mid–2021, most emerging economies, including Russia, had reached pre-pandemic levels. It is shown that most forecasts agree that in 2021 (and partly in 2022) there will be an accelerated recovery and then the main macroeconomic indicators will return to pre-recession trajectories. At the same time, the changes in consumer preferences and business models triggered by the pandemic can lead to sustainable shifts in the sectoral structure of economies.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".