Quantifying the Macroeconomic Effects of the COVID-19 Lockdown: Comparative Simulations of the Estimated Galí-Smets-Wouters Model
Bibliographic record
Abstract
This paper considers 3 scenarios regarding the duration of the COVID-19 pandemic lockdown, staying for 1, 2 or 3 quarters, and 2 types of exceptionally rare and devastating disruptions in employment modeled as adverse labor supply shocks, a temporary one with negligible loss in the labor force due to deaths or a permanent one, with significant loss from deaths. The temporary labor supply shock simulations delimit a lower bound, designed to match about 1/4 of the labor force unable to work, and an upper bound, matching about 3/4 of the labor force made economically inactive, broadly consistent with estimates. The permanent labor supply shock is designed to match, in 3 scenarios again, up to 1% loss of the labor force due to mortality, twice milder than the Spanish flu 2% death rate. Estimated calibrations of the Galí-Smets-Wouters (2012) model with indivisible labor for 5 major and most affected by the COVID-19 pandemic economies are simulated: the US, France, Germany, Italy and Spain. The simulations suggest that even in the most optimistic scenario of a brief (lasting for 1 quarter) and mild (with 1/4 of the labor force unable to work) lockdown, the loss of per-capita consumption (6-7% in annualized terms down from the long-run trend in the impact quarter) and per-capita output (3-4% down) will be quite damaging, but recoverable relatively quickly, in 1-2 years. In the most pessimistic simulated scenario of temporary loss the effects will be 10-15 times more devastating, and the loss of output and consumption will persist beyond 10-15 years. Permanent loss of up to 1.5 percentage points of per-capita consumption and output characterizes the simulated permanent labor supply shock.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| 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".