Early Withdrawal of Pandemic Unemployment Insurance: Effects on Employment and Earnings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We examine the effects of the sudden withdrawal of expanded pandemic unemployment benefits in June 2021 using anonymized bank transaction data for 16,253 individuals receiving unemployment insurance (UI) in April 2021. Comparing the difference-in-differences between states withdrawing and retaining expanded UI, we find that UI receipt falls 36.3 p.p., while employment rises by only 6.8 p.p. by early September. Average cumulative UI benefits fall by $2,529, while average cumulative earnings increase by only $292. Heterogeneity by unemployment duration implies that these effects are primarily driven by extensive margin expiration of benefits rather than by intensive margin reductions in the benefit level.
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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 | 0.000 | 0.000 |
| 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 it