IMPLICATIONS OF THE COVID-19 PANDEMIC FOR STATE GOVERNMENT TAX REVENUES
Bibliographic record
Abstract
We assess the COVID-19 pandemic’s implications for state government sales and income tax revenues. We estimate that the economic declines implied by recent forecasts from the Congressional Budget Office will lead to a shortfall of roughly $106 billion in states’ sales and income tax revenues for the third quarter of 2020 through the second quarter of 2021 (the 2021 fiscal year for most states). This is equivalent to 0.5 percent of gross domestic product and 11.5 percent of our pre-COVID sales and income tax projection. Additional tax shortfalls from the second quarter of 2020 (the final quarter of most states’ 2020 fiscal years) may amount to roughly $42 billion. We discuss how these revenue declines fit into several pieces of the broader economic context. These include other revenues (e.g., university tuition and fees) that are also at risk, as well as spending needs necessitated by the public health crisis itself. Further dimensions of context involve fiscal support enacted through several pieces of federal legislation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".